Best Locations to Start a Vacation Rental Business

The best location for a vacation rental is not a town on a list — it's a market that clears a regulatory screen, has demand you can verify with public data, and pencils out against a realistic (not aspirational) revenue number after you've priced in seasonality, cleaning logistics, and your own drive time. If you're picking a market by reading a "top eight towns" post from a few years ago, you're underwriting a deal with someone else's stale assumptions instead of your own math.

I've run short-term rental properties since 2016 and been in real estate since 2008. I've watched operators buy in "hot" markets that a blog told them about, only to find out six months later that the city capped permits, the HOA banned rentals under 30 days, or the "median revenue" figure they'd seen was three years old and from a completely different property type. The town never mattered as much as the process they skipped to get there.

This is that process. It's a market-selection framework you run yourself, in order, with sources you can check today — not a shortlist that ages the moment it's published. Run it on the market you already own property in, too; regulatory and demand conditions change under an existing property just as much as they change under a candidate you haven't bought yet, and re-scoring an existing hold once a year is cheap insurance against a change you'd otherwise learn about from a code enforcement notice.

Why "Best Cities for Airbnb" Lists Expire Fast

A location list is a snapshot. Short-term rental demand, local ordinances, and comparable pricing all move on their own timelines, and none of them move together. A town can look great on a 2020 list and be functionally closed to new short-term rental licenses a few years later — Maggie Valley, Sevierville, Hot Springs, the Poconos, Big Sky, Dauphin Island, St. Augustine, Killington, and Surfside Beach have all shown up on that kind of list, and every one of them sits in a state or county that has revisited short-term rental rules at least once since the pandemic-era rental boom that generated most of those articles in the first place. None of this is a knock on those towns specifically — it's the nature of any list built from a moment in time and never revisited. Treat any pre-2023 town-by-town ranking, including the older version of this exact article, as a history lesson about what one writer saw once, not as current underwriting data.

The bigger problem isn't that the towns changed. It's that most of those articles cited median home prices and "average monthly revenue" figures with no attribution — no MLS pull date, no AirDNA or PriceLabs export, no sample size, no property type. A number with no source is a number you cannot verify, and a number you cannot verify is a number you should not underwrite a mortgage against. If a market-selection article can't tell you where its number came from and when it was pulled, treat every figure in it as illustrative at best and discard it at worst.

That's the standard this framework holds itself to: every data point below is either sourced to a named public dataset or explicitly flagged as an illustrative example. Nothing here is a number to plug into your own model without re-verifying it locally, on the exact parcel and property type you're considering.

Screen Regulation Before You Screen Demand

Most new operators reverse this order — they fall in love with a market, then discover the regulatory reality after they've already put money down. Screen regulation first. It's the fastest, cheapest kill-switch available to you, and it eliminates markets in an afternoon that would otherwise cost you weeks of underwriting on a deal you were never legally able to close.

Four things to check for any candidate market, in this order:

1. City or county short-term rental ordinance. Search the municipality's codified ordinances (most cities publish through Municode or a similar library) for terms like "short-term rental," "transient occupancy," or "vacation rental permit." Look specifically for a permit cap, a primary-residence requirement, a minimum-stay rule, or a moratorium on new licenses.

2. HOA or condo association rules, if the property sits inside one. An HOA can prohibit rentals under 30 days even where the city allows them, and that restriction usually isn't visible until you pull the CC&Rs from the association directly, not from a listing agent's summary.

3. Owner-occupancy requirements. A growing number of cities only permit short-term rentals in an owner's primary residence, which eliminates pure investment-property plays entirely and changes the entire return profile of the deal.

4. Licensing capacity and waitlists. Some markets technically allow short-term rentals but have capped the number of active licenses and closed the waitlist. That's a market where you can buy the real estate and still never legally operate it as a short-term rental.

Illustrative example, not current guidance for any specific town: picture a coastal market that permits unlimited non-owner-occupied short-term rentals in one year, then caps total licenses two years later and freezes new applications the year after that — a short window in which the rules on the same parcel changed twice, with no changes to the property itself. That's exactly why the underwriting has to start with a phone call or a code search today, not a memory of what a market allowed when a blog post was written.

If a market fails this screen, stop. Don't move to the demand analysis. A great demand profile in a market that won't issue you a permit is not an opportunity — it's a research exercise that costs you time you could spend on a market that actually clears.

Verify Demand With Public Data, Not Anecdote

Once a market clears the regulatory screen, verify that people are actually traveling there, and why, using data you can pull yourself rather than a claim someone else made in an article. Three public, checkable demand drivers:

• National or state park visitation. If the market sits near a park, the National Park Service publishes visitor-use statistics by park and by year. Rising or stable multi-year visitation is a real demand signal; a market riding a single spike year is not, and the difference matters enormously to a five- or ten-year hold.

• Airport enplanements. The FAA publishes annual passenger boarding data by airport. A regional airport with growing enplanement counts over a multi-year trend tells you people are choosing to fly into that area on their own dime — a more durable signal than a single viral summer or a social media trend.

• Recurring event and institutional calendars. University academic calendars (move-in weekends, graduation, football Saturdays), fixed annual events (a race, a state fair, a marathon), and hospital or corporate campuses that generate recurring mid-term travel are all demand you can verify against a public calendar rather than take on faith from a listicle.

None of these tell you the exact nightly rate you'll achieve. They tell you whether the demand story is real and recurring versus a single good season that a listicle happened to capture and never revisit.

Supply, Seasonality, and a Realistic Revenue Range

A market can have strong demand and still be a bad buy if supply has already caught up to it, or if the demand is concentrated in eight weeks a year with nothing to support the property the rest of the time. Two supply-side checks come first:

• Active listing growth. If the number of active short-term rental listings in a submarket has grown faster than visitation or population over the same period, you're underwriting into rising competition, not rising demand — and pricing power will erode faster than a stale article's revenue estimate assumed.

• Seasonality concentration. A ski town with a five-month season and a beach town with a seven-month season carry very different fixed-cost math. Ask what percentage of realistic annual revenue would need to come from the peak 90 days, and stress-test your mortgage and management costs against the shoulder and off-season months specifically — not the annual average, which hides exactly the risk you're trying to underwrite.

Once supply and seasonality are understood, build a revenue range instead of a point estimate, and source it to data you pulled yourself: a PriceLabs or AirDNA market report, a Rabbu estimate, or a direct pull of ten to fifteen comparable active listings in the exact submarket, filtered by bedroom count and property type. A single "average monthly revenue" figure with no range, no seasonality breakdown, and no comparable set is exactly the kind of number that made the old town-by-town lists unreliable in the first place.

Hold that revenue range against your full cost basis: acquisition price, expected financing terms, property taxes, insurance (short-term rental policies typically run higher than standard landlord policies), furnishing, and ongoing management. The SBA's 7(a) program terms and current mortgage guidance are both public and change over time, so re-check current rates rather than anchoring to a number you saw months ago in someone else's spreadsheet. If the realistic low end of your revenue range doesn't cover debt service plus operating costs with room for a vacancy buffer, the rest of the market analysis is academic — the deal doesn't work regardless of how appealing the town is.

The Operations-Distance and Cleaner-Supply Test

A market can pass regulation, demand, and revenue math and still be operationally unworkable for you specifically. Two final checks that are about your operating model, not the market in the abstract:

• Drive time and response capability. If you're self-managing, how far are you from the property, and can you realistically respond to a lockout, a maintenance failure, or a same-day turnover issue? Remote self-management across a multi-hour drive is one of the most common reasons first-time operators underperform their own projections — not because the market was wrong, but because the operating model didn't fit the distance and something broke on a Friday night three hours away.

• Cleaner and maintenance labor supply. Call two or three local cleaning companies and a handyman before you buy, not after. A market with strong tourist demand but a thin local labor pool for short-term-rental-specific turnover cleaning will cap your booking calendar regardless of how strong demand looks on paper, because you simply cannot turn units fast enough between guests.

The Scoring Rubric: Run Every Candidate Market Through the Same Grid

Score each candidate market on the same five criteria before comparing them side by side. Any market that fails a kill-switch condition should be dropped regardless of its score on the others — a kill-switch failure isn't a deduction, it's a disqualification.

Illustrative scoring example, not a real market: a candidate market might score well on demand durability (rising airport enplanements three years running) and revenue math, but fail the regulatory kill-switch because the city closed new short-term rental applications the prior year. That market gets dropped before it's ever compared to alternatives, regardless of how attractive the other four criteria look on paper.

Public Data to Pull Before You Compare Markets

Use this table as a checklist. Each source answers one specific question in the rubric above — pull all of them for a candidate market before you rank it against alternatives, and re-pull them any time you're revisiting a market you scored more than a few months ago.

How to Sanity-Check a Market's Revenue Claims

Any time you read a market-selection article — including this one, and definitely the older "top eight towns" style posts — ask three questions before you act on a single number in it:

1. What's the source and the pull date? "Average revenue of $X per month" with no citation to AirDNA, PriceLabs, MLS, or a named dataset is not a number, it's a guess dressed up as one.

2. What's the sample size and property type? A market average across two hundred listings of every bedroom count tells you almost nothing about what your specific three-bedroom, non-waterfront property will earn.

3. Has anything changed since publication? Ordinances, license caps, and supply all shift faster than most articles get updated. A number from a few years ago describing conditions from a few years ago is a history lesson, not underwriting data for a purchase you're about to make.

If an article can't answer those three questions, treat its numbers as illustrative at best, and go pull your own comps before you write an offer. Then take a concrete next step: pick two or three candidate markets this week, spend thirty minutes on the municipal code search for each, and spend one afternoon pulling comps and public demand data using the sources above. Score them against the rubric, drop anything that fails a kill-switch, and compare what's left on realistic revenue range versus your actual cost basis — not a listicle's headline number.

If you want a second set of eyes on the math before you commit capital, that's exactly what our complimentary one-on-one diagnostic call is for — we'll walk your specific candidate markets and numbers together, and if it makes sense to go deeper, our $997 action plan lays out the exact underwriting and operating steps for the market you choose. Related reading on our site: how to choose your first STR market, the SOAR framework for evaluating any STR opportunity, and what to check on permit contingencies before you close.

Frequently Asked Questions

Sources

• National Park Service — visitor-use statistics

• FAA — airport passenger boarding (enplanement) data

• U.S. Census Bureau — American Community Survey data

• SBA — 7(a) loan program terms

• IRS — Topic no. 415, renting residential and vacation property

• Municode Library — search municipal short-term-rental ordinances