Choosing your first short-term rental market is a research job, not a hunch: check the local permit rules first, then real booked demand, competing supply, the shape of the season, your all-in cost basis, and whether you can actually staff turnovers there. Six data points, checked in that order, because the first one can disqualify a market before you spend another hour on it.
I've spent 18+ years in real estate, focused on short-term rentals since 2016, and trained more than 10,000 operators through CashFlowDiary. The first-market mistake almost never looks like a bad market on paper. It looks like a good market where the operator checked the numbers before checking the rules, or checked annual averages instead of month-by-month demand, or bought a house 40 minutes past where any cleaner will drive on a Sunday.
Why the Order Matters More Than the Data
Most first-time buyers start with a revenue estimate. That's the last thing you should look at, because a revenue estimate is a model output — it inherits every assumption underneath it, and it tells you nothing about whether your unit would be legal.
Regulation is binary. Either the city issues a permit for the use you plan, or it doesn't. No occupancy figure survives a "no permits in residential zones" ordinance. So regulation goes first, and everything else is a screen you run only on markets that survive it.
The other five points are gradients. A market can be thin on supply and still work if the season is long. It can be expensive and still work if the cost basis is low relative to booked nights. You're not looking for a perfect market. You're looking for one where you can name the failure mode before you own it.
Order | Data point | What it decides | Kill condition |
|---|
1 | Regulation and permits | Whether your plan is legal at all | Permit not issued for your zone or unit type |
2 | Real booked demand | Whether guests are actually paying | Fewer than ~150 booked nights/year in comparable units |
3 | Competing supply | Whether you can win nights | Active listings growing faster than booked nights |
4 | Seasonality shape | Whether cash flow survives the trough | Trough months can't cover debt plus fixed costs |
5 | Cost basis | Whether the math has room to be wrong | No positive case at a 15% demand haircut |
6 | Operating reality | Whether you can run it every week | No cleaner willing to service the address |
The kill conditions above are the thresholds I use as a screen, not published industry benchmarks. Set your own and write them down before you look at listings.
Data Point 1: Regulation and Permits (Check This First)
Go to the city or county website and find the actual ordinance or licensing page, not a summary blog post. Nashville publishes its short-term rental permit types and rules on the city Codes department site; Austin publishes its license classes and requirements through the city's short-term rental page. Those are the documents that govern you.
Read for five things: whether non-owner-occupied rentals are permitted, whether permits are capped or zone-limited, whether there's a minimum-night rule, what the occupancy and parking limits are, and what happens at renewal. Then call the planning or licensing desk and ask one question: "If I buy at this address today, can I get a permit, and how long is the queue?" Write down the date, the person's name, and the answer.
Also check the direction of travel. Search the city clerk's site for recent council agendas and minutes mentioning short-term rentals. A market with a pending moratorium is a different asset than a market with a stable licensing program, even if today's rules read the same.
Platform terms are a secondary check, not a source of law. Airbnb's terms of service put the obligation on the host: you are responsible for knowing whether your jurisdiction requires you to register, get a permit, or obtain a license before listing. Use the platform's local-rules prompts to confirm you haven't missed a registration step, then verify against the ordinance itself.
This is not tax or legal advice. Before you close, have a local attorney read the ordinance against your specific address and plan.
Data Point 2: Real Booked Demand, Not Average Occupancy
Occupancy percentages hide the number you care about: booked nights. A listing that was only available 90 nights can post a high occupancy rate and still be a hobby. Ask for booked nights per year on units that match yours in bedroom count, and look at the distribution, not the average.
Where the data comes from matters. Market data vendors estimate demand from scraped calendars, and a blocked calendar night can be an owner stay, a maintenance block, or a booking. AirDNA documents how its metrics are built in its help center — read that before you treat any single figure as observed fact. Pull the same market from two vendors; if they disagree by a wide margin, treat the market as unmeasured rather than good.
Then verify by hand. Open the platforms as a guest, search a mid-week date six weeks out and a weekend date four months out, and count how many comparable units are already taken. Repeat for a shoulder month. Ten minutes of that will tell you more about the depth of demand than a downloaded export.
Finally, name the demand drivers and check their calendars. One employer, one festival, or one stadium is a single point of failure. Three independent drivers that peak in different months — a university, a hospital system, a regional tourist draw — is what durability looks like.
Data Point 3: Competing Supply and Where It's Going
Supply is the variable that quietly resets your rate. Count active listings today, count them 12 months ago, and compare that growth rate to the growth in booked nights over the same period. If listings grew faster than demand, expect rate pressure regardless of how the market looked last season.
Look at the top of the market too. If the best-performing listings are professionally furnished four-bedroom homes with hot tubs and yours would be a plain two-bedroom, you are not competing with the market average — you are competing with the units a guest sees on page one.
Supply signal | Where to get it | Encouraging | Discouraging |
|---|
Active listing count, 12-month change | Market data vendor, cross-checked | Flat or slower than demand growth | Double-digit growth with flat demand |
Permit issuance trend | City licensing page or open-data portal | Capped or stable | Newly uncapped, fast issuance |
Amenity baseline | Top 20 listings on-platform | You can match it in budget | Hot tub plus pool table is table stakes |
Housing stock and household data | Census ACS and data.census.gov | Growing population, tight rentals | Shrinking population, high vacancy |
Pricing behavior | Weekend rates 60 days out | Rates holding | Widespread discounting midweek |
Public housing data is worth an hour here. The American Community Survey gives you population change, household counts, and rental vacancy by place — the context that tells you whether new supply is being absorbed by real growth or just stacking up.
Data Point 4: The Shape of the Season
Annual averages lie in both directions. Build a 12-row month-by-month table for the market: typical rate, typical booked nights, and the resulting gross for a comparable unit. Then look at the trough, not the peak.
The question is simple. In your two worst months, does gross revenue cover debt service, utilities, insurance, software, and the cleaning cost of the nights you do book? If it doesn't, you need reserves sized to the gap times the number of trough months, in cash, before you close. Seasonal markets aren't bad. Unfunded seasonal markets are.
Three shapes show up repeatedly:
Long plateau — eight to ten strong months, a short trough. Easiest first market.
Sharp peak — three months carry the year. Workable with reserves and a mid-term rental plan for the off-season.
Two peaks — summer and a winter holiday, with two deep shoulder troughs. Requires the most planning and the most discipline on rate.
Also check whether the peak is weather-dependent. A ski or hurricane-exposed market adds a variance you can't price away.
Data Point 5: Cost Basis, Stress-Tested
Cost basis is the one input you control at purchase. Two operators in the same market with the same unit can have opposite outcomes because one paid less and furnished tighter.
Write out the all-in number: purchase price, closing, furnishing, photography, the permit fee, and 90 days of operating reserve. Then model three cases — the vendor estimate, that estimate cut 15%, and that estimate cut 30%. If only the first case works, you don't have a deal, you have a bet on someone else's model.
Compare the same unit against its long-term rent. If the short-term gross doesn't clear long-term rent by a meaningful multiple after cleaning, supplies, platform fees, and higher utilities, the extra work isn't paying you. That comparison is worth running explicitly rather than assumed.
Data Point 6: Operating Reality, and When to Walk
The sixth data point isn't in any export. It's whether the market can be operated by you, from where you live, with the vendors who exist there.
Phone the cleaners before you write an offer. Same-day turnover on a Sunday in August is the hardest thing you will buy, and in tight labor markets it's the constraint that caps your calendar. Ask what they charge per turn, whether they carry insurance, whether they'll do linens, and what their cancellation policy is. Ask a handyman how fast they respond to a water leak. Ask a lock vendor whether anyone services the property.
Then set your disqualifiers in writing before you get attached to a house:
Permit cannot be issued for the address and unit type, or issuance is paused.
Comparable units are below the booked-night floor you set.
Listings grew double digits while booked nights were flat.
Trough months don't cover fixed costs and you don't have the reserve in cash.
No positive case at a 15% haircut to the demand estimate.
No cleaner will commit to Sunday turnovers at your address.
Any one of those is a stop, not a negotiation point. The reason to write them down first is that every market produces a story for why this deal is the exception.
How to Screen a Market: A Six-Step Process
Pull the ordinance and licensing page for the city and the county, read them, and call the licensing desk. Record the answer and the date. Stop here if the answer is no.
Pull booked nights for comparable units from two data sources, then hand-verify availability on-platform for one peak, one shoulder, and one trough date.
Count active listings now and 12 months ago; compare against demand growth and check permit issuance trend.
Build the 12-month rate and booked-night table; size the trough gap and the reserve it implies.
Model your all-in cost basis at the vendor estimate, minus 15%, and minus 30%. Keep only markets that survive minus 15%.
Call three cleaners and one handyman in the market. Ask for Sunday turnover availability, rate per turn, and how far they'll drive. No coverage, no deal.
Run this on three markets, not one. The comparison is what makes the decision obvious, and it usually takes four to six hours per market when done properly and not skipped.
If you want a second set of eyes on the three markets you're screening, book a complimentary one-on-one diagnostic call at https://cashflowdiary.com/diagnostic/ and bring your numbers.
Frequently Asked Questions
How long should market research take before I buy?
Plan on four to six hours per market if you're doing it properly, spread over a week so you can get callbacks from the licensing desk and from cleaners. Screening three markets that way is a realistic two-week project, and it's the cheapest two weeks in the whole purchase.
Should I invest in my own city or a destination market?
Start where you can drive to the property within a couple of hours unless the operating team is already in place. Proximity fixes problems that remote ownership turns into refunds. A destination market can be the right second purchase once you've built the vendor bench.
Is AirDNA data reliable enough to buy on?
Treat it as a screen, not as evidence. Vendor metrics are modeled from platform calendars, which is why the help documentation explains how the estimates are built — read it, cross-check a second source, and confirm by hand-searching availability on real dates before you rely on any figure.
What counts as too much supply growth?
Compare growth rates, not counts. If active listings grew faster than booked nights over the last 12 months, rates are likely to soften, and a first unit without a distinctive amenity set is the one that absorbs that softening.
Can a highly seasonal market work for a first unit?
Yes, if the reserve is funded before closing and you have an off-season plan such as mid-term rentals to traveling professionals. What fails is a seasonal market bought on an annual average with no cash set aside for the trough.
What if the city changes the rules after I buy?
Assume it can happen and buy accordingly: prefer addresses that still work as a long-term or mid-term rental, keep your permit paperwork current, and follow the council agenda in your market. That optionality is a real part of the underwriting, not a footnote.
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