Airbnb Occupancy Rates By City

In Q1 2026, I pulled my Columbus GA property's numbers and found 58% occupancy — right at what I'd expected for the market. The problem wasn't the number itself. It was that I had no idea whether 58% was good or embarrassing for that zip code. A host in my BiggerPockets STR thread was hitting 72% a few miles away. Same city, same bedroom count, similar price point. What was I missing?

That question — what's a good occupancy rate for my market — is one of the most practically useful things you can understand as a short-term rental host. Not just for benchmarking, but for pricing decisions, listing audits, and knowing whether to keep a property or sell it.

What STR Occupancy Rate Actually Means

Occupancy rate = nights booked ÷ nights available. Simple math. But the devil is in the denominator. Some data sources count only nights you've listed (excluding blocked dates). Others count every calendar night. When comparing your rate against a city benchmark, make sure you're measuring the same thing — otherwise you're comparing apples to locked-out nights.

Most published city benchmarks use available nights as the denominator — nights where your calendar is open, not blocked for personal use. If you block two weeks in December, those nights shouldn't tank your reported occupancy. AirDNA and similar tools normalize for this. Your Airbnb Performance tab does not — it counts all calendar nights.

Airbnb Occupancy Rates by City: 2025–2026 Benchmarks

These are annual average ranges drawn from aggregated STR analytics data as of late 2025 and early 2026. Individual months swing hard, especially in seasonal markets — I'll address that separately.

These ranges draw from aggregated AirDNA market data, Mashvisor reports, and published research from Skift's short-term rental coverage. Your specific neighborhood, bedroom count, and amenity set will push you above or below these ranges.

Why Your City's Baseline Changes Your Entire Pricing Strategy

If the Smoky Mountains average is 72% and you're at 65%, you have a gap to close — probably a calendar-visibility fix or minimum-night adjustment gets you most of the way there. But if you're in Columbus GA hitting 55% and the market ceiling is 56%, you've essentially maxed out the market. The right move isn't to optimize harder. It's to push ADR instead of occupancy.

This is what city-level data actually gives you: it tells you which lever to pull. There are two ways to grow revenue in STR — fill more nights, or charge more per night. In saturated markets, the second one is usually the higher-use play. In under-optimized markets, the first one is. Without knowing where your market sits, you're pulling levers blind.

How to Use Occupancy Benchmarks Practically: 5 Steps

1. Pull your trailing 90-day occupancy. Your Airbnb host dashboard under Performance → Occupancy shows this. If you use a PMS like Hospitable ($29–$99/mo), export from there for cleaner data. Don't use trailing 365 if you bought or significantly renovated in the past year — you'll dilute the sample with non-representative months.
2. Find your market's benchmark. AirDNA's market overview (free tier gives a rough city number; paid tiers give zip-code-level breakdowns) is the most reliable source for Airbnb-specific data. The BiggerPockets STR forums also have active local market threads where hosts share real numbers. Combining both sources gives you a cross-check.
3. Calculate your gap and its direction. If you're 8+ points below market, you're leaving occupancy on the table. If you're at or above market, stop trying to fill nights and start raising rates during soft periods instead.
4. Check RevPAR, not just occupancy. Revenue per available room (ADR × occupancy rate) is the real metric. A host doing 60% at $220 ADR earns more than one doing 75% at $140. I know Columbus GA hosts hitting 70% occupancy at $79/night, burning out for $1,600/month gross. That's not a win.
5. Audit your minimum-night settings. High minimums kill occupancy in most non-resort markets. In Columbus GA, a 3-night minimum cost me roughly 12 percentage points of occupancy — I was turning away Monday–Wednesday business travel gaps. Dropping to 1-night for weekdays added about $400/month in revenue within 60 days.

Seasonal Swings: The Number Nobody Posts

Annual averages are useful for long-term strategy. Monthly data is what you need to actually run a listing.

In the Smoky Mountains, occupancy can run 85–90%+ in October (leaf season) and drop below 55% in January. That 72% annual figure masks a 35-point seasonal swing. If you're pricing flat year-round, you're selling October too cheap and sitting empty in January because you're still anchored at fall rates.

Austin's annual 55–63% average hides the fact that SXSW week in March can push $500+/night with near-100% occupancy, while mid-July might run 40% at $110. If you don't have dynamic pricing active before SXSW, you're guaranteed to leave money behind — every year, without exception.

Common Mistakes Hosts Make With Occupancy Data

Chasing 100% occupancy. Almost always a pricing error. If you're consistently booked 90+ days out at 95%+ occupancy, your rates are too low. You're selling future inventory cheap. Raise rates until your 30-day forward occupancy drops to around 70–75% — that's usually where you maximize revenue without leaving unsold nights.

Comparing against the wrong cohort. A 1-bedroom condo should not be benchmarked against a city average that includes 5-bedroom vacation cabins. AirDNA and Mashvisor both let you filter by bedroom count and property type on paid tiers. Do that before drawing any conclusions.

Ignoring quality of nights booked. Filling your calendar with back-to-back 2-night weekend stays at $95 ADR can look great on occupancy but might be blocking full-week bookings at $130 ADR. Run both revenue scenarios before assuming more occupancy always means more money.

Where This Gets Harder at Scale

Once you're managing more than 3–4 properties across different markets, manually tracking occupancy benchmarks by city gets genuinely unwieldy. You end up with a spreadsheet with tabs for each city, pulling from different data sources, and it's already stale by the time you review it. I've been there.

PriceLabs' Market Dashboard starts making more sense at that point. It pulls market-level occupancy signals and adjusts rate recommendations automatically. The recommendations still need a human sanity check — I've seen it suggest rates during local event weekends that were either too aggressive or clearly too conservative — but it solves the scale problem better than manual tracking does.

If you're comparing Koohost against something like Hostaway (custom pricing, typically $125+/mo at the mid tier) specifically for market analytics, the honest answer is that enterprise PMS tools generally have more built-in market benchmarking. Where Koohost wins is on price and all-in-one automation for portfolios under 20 properties.

How Koohost Surfaces Your Occupancy Numbers

I built Koohost partly because I was tired of toggling between five dashboards to understand what was happening across my portfolio. The statements view shows occupancy by property, ADR, RevPAR, and average booking lead time — all from the same data sync that drives guest messaging and lock automation. No extra data entry, no separate analytics subscription.

What Koohost doesn't do — and I'll say this plainly — is provide city-level market benchmarks. For that you still need AirDNA or PriceLabs. Koohost shows you your numbers clearly. Market comparison still requires an external tool. That's a real gap I plan to close, but I'd rather tell you that now than oversell what's there today.

For hosts using Hospitable, Lodgify, Smoobu, or iCal feeds, occupancy data flows in automatically through the PMS integration. The Pro Host plan ($30/mo) includes the full analytics dashboard with occupancy, ADR, and RevPAR by property. Solo Host ($15/mo) gives you a lighter version via iCal sync — booking counts and calendar visibility, but not the full financial breakdown.

If you're trying to recover nights that fall through calendar gaps, the messaging automation in Koohost handles gap-fill outreach to guests already booked and automated inquiry responses that convert better than a 3-hour manual reply lag.

Smart Home as an Occupancy Driver

When I added a Yale Assure 2 on one property and a Schlage Encode on another and automated the check-in experience end to end, my Airbnb review scores for check-in specifically went from 4.7 to 4.9 within three months. Higher check-in scores feed into Airbnb's search ranking algorithm. Better ranking means more impressions. More impressions at a competitive price means higher occupancy. The smart lock upgrade isn't separate from the occupancy conversation — it directly feeds it.

Running a Nest 3rd-gen or ecobee SmartThermostat Premium tied to your booking calendar and switching to eco-mode between reservations cuts roughly $40–$80/month per property in utility costs depending on your climate. That's RevPAR improvement through cost reduction rather than rate increases. Koohost handles the thermostat vacation-mode switching automatically based on reservation gaps — the management software integration means no manual configuration per booking.

For a full breakdown of how Koohost compares against other tools on this exact combination of analytics, smart home, and messaging, the Hospitable alternative page covers what makes sense at different portfolio sizes and price points.

FAQ

What is a good occupancy rate for Airbnb?

It depends on your market. Nationally, the STR average is around 56%. In high-demand markets like Nashville or the Smoky Mountains, 65–75% is realistic. In smaller secondary markets like Columbus GA, 50–58% can be at or near the market ceiling. The more useful question is how your rate compares to local competitors in the same bedroom count and property type — not against a national average.

How do I find occupancy rates for my specific city?

AirDNA's free market overview gives a rough city-level number; paid tiers break it down by zip code and bedroom count. Mashvisor and Rabbu offer similar data. The BiggerPockets STR forums have active market-specific threads where local hosts post real numbers. Cross-referencing two sources gives you the most reliable picture. For Airbnb-specific data (as opposed to all platforms), AirDNA is generally the most accurate.

Is 70% occupancy good on Airbnb?

In most markets, yes — 70% is strong. But context matters. If your market average is 72%, you're slightly below benchmark and there's room to improve. If the market ceiling is 65%, you're already outperforming and should be raising ADR rather than pushing occupancy higher. Run the RevPAR calculation (ADR × occupancy) before deciding which lever to pull — occupancy alone doesn't tell you if you're making good money.

Which cities have the highest Airbnb occupancy rates?

Based on 2025–2026 aggregated data, top performers include the Smoky Mountains (68–75%), New Orleans (63–72%), Miami and Fort Lauderdale (60–70%), and Nashville (62–68%). These markets have high leisure demand, event-driven spikes, and year-round tourism bases. Worth noting: the highest occupancy markets often also carry the strictest short-term rental regulations — factor that into any acquisition decision.

How do minimum-night settings affect occupancy rate?

Significantly. In most non-resort, non-vacation-destination markets, a 3-night minimum will cost you 10–15 percentage points of occupancy by blocking gap nights — the Monday–Thursday stays that fill the spaces between weekend bookings. Dropping to 1-night minimum for weekday arrivals while keeping a 2-night minimum for Friday–Saturday arrivals is often the highest-ROI calendar setting change you can make. Test it for 60 days and measure the delta.

Should I prioritize occupancy rate or ADR?

Depends where you are relative to your market ceiling. If you're 8+ points below market occupancy, fix that first — there's demand you're not capturing, likely due to calendar settings, response time, or listing quality issues. If you're at or above market occupancy, stop trying to fill nights and push ADR instead. Revenue = ADR × occupancy, and in saturated markets, ADR is the higher-use variable. Track RevPAR monthly, not occupancy in isolation.

Does Airbnb's algorithm reward higher occupancy?

Indirectly. Airbnb's search ranking weights acceptance rate, response time, review scores, and listing completeness — not raw occupancy directly. But higher occupancy generates more reviews faster, which feeds the ranking algorithm. Fast response time and high acceptance rate (which correlate with occupancy) are direct ranking inputs. So optimizing for occupancy and optimizing for search ranking largely push you in the same direction.

Want to track your occupancy, ADR, and RevPAR alongside guest messaging and smart home automation from one dashboard? Try Koohost free for 30 days — no credit card.