Airbnb Occupancy Rate Benchmarks: What's Normal for Your Market?

A 58% occupancy rate in Sedona is underperforming. The same number in downtown Chicago is average. Here are the market-specific benchmarks serious STR operators actually use.

Your occupancy rate is meaningless without a benchmark. A 58% occupancy rate in Sedona, Arizona is a slow month that warrants an urgent pricing and listing audit. The same number in downtown Chicago is roughly average for the market. Operators who don't know their market's specific baseline are managing blind — measuring themselves against a number that tells them nothing about whether they're winning or losing.

The common mistake is to Google "average Airbnb occupancy rate" and find some national figure — which in 2025 sits at around 54.2% median across all US short-term rentals according to AirDNA's annual State of STR report. That number is so aggregated as to be nearly useless for any individual operator. It blends beach houses with ski cabins, urban apartments with rural retreats. The only number that matters is the occupancy benchmark for your specific market type, your property class, and your operating strategy.

Why National Occupancy Averages Mislead Multi-Property Operators

National averages disguise enormous variance. According to AirDNA's 2025 market data, the top 10% of markets by occupancy rate averaged 76.4% in 2025. The bottom 10% averaged 31.8%. That 44-point spread sits inside the same national average figure every time someone cites it. If your properties span multiple markets — which is common for operators with 5+ doors — comparing your portfolio-wide occupancy to a national average is doubly misleading, because you're averaging across averages.

The more actionable framework: establish a benchmark for each market where you operate, then compare each property in that market against the local median and the top-quartile threshold. Your floor goal should be the local median — don't trail the average operator. Your stretch goal should be the top quartile — perform like the best-run properties in your comp set. The gap between those two numbers is where your operational and pricing decisions live.

Occupancy Benchmarks by Market Type

Here are the occupancy ranges serious STR operators use as reference points, based on aggregated 2025 market data from AirDNA and industry benchmarking from STR Insights' 2025 annual operator report.

Beach and Coastal Markets

Beach and coastal markets produce the widest seasonal swings of any STR market type. Annual occupancy for well-managed properties averages 65–75%, but that number conceals months of 90%+ occupancy in summer alongside winter lows of 35–45%. AirDNA's 2025 data shows the Outer Banks, NC averaged 68.3% annually; Myrtle Beach, SC averaged 71.2%; and Gulf Shores, AL averaged 67.8%. These markets have extremely high peak demand but require careful off-season strategy to sustain a healthy annual number.

The key distinction in beach markets is that occupancy is often demand-constrained in peak but rate-constrained in shoulder. Most beach properties can fill to 95%+ in July with any reasonable rate. The operators who separate themselves set aggressive rates in peak — instead of accepting every booking that comes in — and build a discount-free shoulder strategy using extended stays and snowbird rates for 30+ day bookings to fill the winter calendar without gutting ADR.

Urban and City Markets

Urban markets produce more consistent year-round demand but rarely reach the seasonal extremes of beach and mountain markets. The 2025 AirDNA urban market median sits at 58–65% occupancy, with Chicago at 61.4%, Dallas at 58.7%, and Seattle at 63.2%. Urban properties benefit from a more diversified demand mix — business travel, weekend leisure, event-driven demand, and extended stays — which smooths the occupancy curve but caps the high-season ceiling.

Urban operators managing 3+ properties often find that the gap between their best-performing and worst-performing properties is larger than the gap between their portfolio average and the market median. A 12-unit urban portfolio with four properties consistently above 70% and four below 50% has a different problem than a portfolio uniformly running 60%. Understanding property-level variance — not just portfolio averages — is what separates sophisticated portfolio management from blind averaging.

Mountain and Ski Markets

Mountain markets are among the most volatile from a seasonality standpoint. Annual occupancy averages 55–70%, but Breckenridge, CO averaged 64.1% annually in 2025 — achieved through 85%+ occupancy during January–March peak ski season and occupancy as low as 22% during April–May mud season. Vail and Aspen trended similarly. For mountain operators, annual occupancy is almost a misleading metric. Managing peak season revenue maximization and shoulder season demand creation are functionally different businesses that happen to use the same property.

The most important strategic question in mountain markets isn't "how do I raise my annual occupancy?" — it's "how do I extend the sellable season on either end of the peak?" Fall foliage, mountain biking, and summer hiking have created genuine demand extensions in markets like Park City, UT and Asheville, NC. Operators who invest in positioning their properties for multi-season appeal consistently outperform single-season operators on both occupancy and annual RevPAN.

Rural and Lake Markets

Rural and lake markets show the widest variance of any category — annual occupancy can range from 38% in oversupplied rural markets to 65% in highly desirable drive-to lake markets. According to STR Insights' 2025 survey, the median rural STR operator ran 47% annual occupancy, but operators in constrained lake markets with limited permit issuance averaged 61%. The critical variable is drive-market proximity: properties within 90–120 minutes of a major metro area command meaningfully higher baseline demand than identical properties further away.

A 58% annual occupancy rate means completely different things in Myrtle Beach versus Detroit. The only number that matters is how your property performs relative to the best operators in your specific market.

The Three Occupancy Thresholds That Actually Matter

Regardless of market type, three occupancy bands drive materially different operational responses. These thresholds don't come from an industry handbook — they emerge from how the STR business actually works financially.

Green: ≥80% occupancy means your property is effectively sold out at the current rate. This is not inherently a success signal. A property running 95% occupancy during peak almost certainly has its rate set too low. Full occupancy at any price is not the goal. Full occupancy at the highest rate the market will bear is the goal. Demand exists at a higher price; you're leaving margin on the table.

Amber: 60–80% occupancy is healthy for most market types and property classes. In this range, the strategic question is ADR optimization, not demand creation. You're filling enough to establish pricing power; the focus should be on pushing the per-night rate rather than hunting for additional bookings.

Red: <60% occupancy requires a root-cause diagnosis before any intervention. Below-60% occupancy in most markets signals one of four things: systematic overpricing, a listing quality problem, calendar issues like excessive owner holds or maintenance blocks eating available inventory, or a genuine demand problem in a soft market. These four causes require four different responses — applying the wrong fix makes each of them worse.

What Pulls Occupancy Down: A Diagnostic Framework

When a property in your portfolio is running below-60% occupancy and the market around it isn't uniformly soft, you have a property-specific problem. The diagnostic question is which of these four causes is responsible.

Systematic Overpricing

A property with below-60% occupancy in a market where comparable properties are filling at 70%+ is almost always overpriced relative to its comp set. The tell: your available nights are browsed but not booked. If your Airbnb listing shows a high view rate but low booking conversion, your rate is the friction point. The fix is to pull your 5–8 most similar comp properties for your target dates, sort by availability, and compare your listed rate against comps that are booking versus comps that aren't.

Listing Quality Issues

Airbnb's search algorithm weighs listing quality heavily — specifically photo count and quality, description completeness, instant booking availability, and response rate. A property with fewer than 15 photos, an incomplete description, or a delayed response pattern gets systematically deprioritized in search. According to Airbnb's 2024 host education data, listings with 20+ high-quality photos receive 24% more views than listings with 10 or fewer. If a property is invisible in search, occupancy problems follow regardless of rate.

Calendar Blocking

Owner holds, maintenance windows, and cleaning gaps all eat into available inventory. Multi-property operators often undercount this because calendar blocks accumulate quietly — a 3-night maintenance block here, a 2-night owner hold there, a cleaning buffer that extends to 2 days. In aggregate, a 7-night monthly block reduces effective annual inventory by 84 nights. When comparing your occupancy to a market benchmark, compare occupied nights against available nights — not total calendar nights.

Genuine Market Softness

Sometimes the market is simply soft. A new hotel opens, supply increases faster than demand, or a major demand driver contracts. If your occupancy is below 60% but your comp set is universally below 60% as well, the problem isn't property-specific — it's a market condition. The responses here are different: rate competition to steal share from weaker properties, positioning for long-stay demand that's less sensitive to market conditions, or portfolio rebalancing toward stronger markets.

Managing Portfolio Occupancy Across Multiple Properties

The challenge for multi-property operators isn't tracking occupancy for one property — it's maintaining clear visibility across all properties simultaneously. A portfolio of 8 properties might have two filling at 82%, three running at 68%, and three stuck below 55%. Without a unified view, the underperformers hide inside a portfolio average that looks acceptable until you disaggregate it.

This is exactly why MagicBnB built the Listings table with health-colored occupancy pills — each property shows green (≥80%), amber (60–80%), or red (<60%) at a glance. Instead of opening 8 separate Airbnb dashboards and manually comparing numbers, an operator can see in three seconds which properties are outperforming, which are underperforming, and which need immediate attention. The properties that would otherwise stay underperforming for weeks while you're focused on operations — those are the ones the color coding surfaces before they cost you a full month of missed revenue.

Combined with MagicBnB's YoY comparison feature, which shows each property's occupancy delta versus the same period last year, operators can distinguish between properties that are structurally declining versus properties in a temporary soft patch driven by seasonality. Those are different problems; managing them as the same problem is how you waste time and money. For a deeper look at how occupancy interacts with ADR and RevPAR in portfolio analysis, see our guide on [RevPAR vs. ADR vs. Occupancy Rate: Which Metric Actually Matters](https://magicbnb.io/blog/revpar-vs-adr-vs-occupancy-rate-which-matters).

Seasonality and Annual Occupancy Strategy

Annual occupancy is a useful summary metric, but operators who optimize it think at the monthly and weekly level — not the annual level. The strategic question for any market is: what does the demand curve look like month by month, and where are the most valuable intervention points?

In beach markets, the intervention points are: (1) capturing maximum rate during peak rather than maximum occupancy, and (2) creating demand in the shoulder through extended-stay minimums and targeted promotions. In urban markets: (1) ensuring listing visibility for event-driven demand spikes, and (2) maintaining competitive rate positioning versus hotels and new Airbnb supply. In mountain markets: (1) fully monetizing the peak ski window, and (2) building genuine off-season demand rather than deeply discounting to fill.

The MagicBnB Portfolio Overview provides week-by-week and month-by-month performance visibility that makes this monthly pattern analysis possible at the portfolio level. When you can see that your mountain properties spike in February but fall off a cliff in April, you have the specific data needed to make a strategic decision — not just a vague sense that spring is slow.

For operators benchmarking their occupancy against external market data, our breakdown of [AirDNA vs Real Data: Why Market Estimates Miss the Point](https://magicbnb.io/blog/airdna-vs-real-data-why-estimates-miss-the-point) covers where market estimates are useful and where your own property data should take priority.

FAQ: Airbnb Occupancy Rate Benchmarks

What is a good occupancy rate for Airbnb?

It depends entirely on your market type. In beach/coastal markets, 65–75% annual occupancy is typical for well-managed properties; top performers reach 80%+. In urban markets, 58–65% is the median; properties with strong listings and competitive pricing hit 70%+. In mountain/ski markets, 55–70% annually is the range, driven heavily by a short but intense peak season. The only reliable reference point is your specific market's comp set — not a national average.

Is 50% occupancy rate good for Airbnb?

In most US STR markets, 50% occupancy is below median and should trigger a diagnostic review. It may indicate overpricing, a listing quality problem, calendar blocking, or a soft market condition. The exception is high-ADR properties in constrained luxury markets where a 50% occupancy rate still produces strong RevPAN because nightly rates are significantly above market average — but this is the exception, not the default interpretation.

What occupancy rate does Airbnb consider successful?

Airbnb doesn't publish a formal occupancy target, but their internal research suggests that properties maintaining 70%+ occupancy with 4.7+ star ratings are positioned in the top 20% of listings by booking performance. Superhost status requires 10+ stays per year with no specific occupancy threshold, but in practice, Superhosts in active markets typically run 65%+ occupancy. The more relevant threshold is your market's top-quartile occupancy — that's the number you should be targeting.

How do I increase my Airbnb occupancy rate?

Start with a root-cause diagnosis before taking action. If occupancy is low because of overpricing, the fix is rate adjustment — not more photos or a better description. If it's a listing quality issue, improve photos and description before touching rates. If it's calendar blocking, audit your available inventory. If it's a genuine demand problem, consider repositioning for extended stays or alternative demand sources like corporate travelers or insurance displacement stays.

Does higher occupancy always mean better performance?

No. A property running 95% occupancy is almost certainly underpriced — you're selling out before the highest-rate travelers even have a chance to book. The goal is not maximum occupancy; it's maximum RevPAN at a sustainable occupancy level. For most market types, 80–90% occupancy at a competitive ADR produces better financial outcomes than 95% occupancy at a rate the market would bear 20% higher.

How do I compare my occupancy to my competitors on Airbnb?

AirDNA's market dashboard provides occupancy data for defined comp sets by market, property type, and bedroom count. Select 5–8 properties that match yours in location, size, and quality tier and track their availability and booking pace over time. A comp that was fully available last week and is now fully booked is revealing something about demand and rate that you can act on. Your own historical data — occupancy month by month for the past 12 months — is the baseline against which all external comparisons should be anchored.

About MagicBnB

MagicBnB (magicbnb.io) gives STR operators real-time occupancy visibility across every property in their portfolio. The Listings table health-colors every property's occupancy pill green (≥80%), amber (60–80%), or red (<60%) so underperforming properties surface immediately — not weeks later in a quarterly review. The YoY comparison feature shows occupancy delta versus the same period last year at both property and portfolio level, making it easy to distinguish structural decline from seasonal variation. The Portfolio Overview tracks week-by-week performance so you can see the occupancy curve that drives your annual number, not just the summary figure. Connect your PMS at magicbnb.io.