Average Airbnb Occupancy Rates by Country

Airbnb occupancy rates by country: key points

Short-term rental professionals often seek country-level benchmarks to assess market health, but the data reveals a critical limitation: Airbnb occupancy rates by country are rarely uniform. Publicly available figures, such as those from AirDNA’s market reports, typically reflect city-specific or regional samples rather than true nationwide averages. For example, Lisbon’s trailing 12-month occupancy stands at 67%, while a rural sample in France’s Occitania region reports just 48%. These disparities underscore how urban density, tourism demand, and regulatory environments create divergent performance profiles within the same country.

Key markets and their occupancy trends

Among the most closely watched destinations, Prague and Oslo emerge as high-utilization markets, with average occupancies of 64% and 59%, respectively. Lisbon leads the sample set at 67%, though its occupancy declined 2.6% year-over-year through May 2026, accompanied by a 3% drop in revenue per available room (RevPAR). In contrast, Bali’s occupancy rose 8% over the same period, yet its RevPAR fell 13.7%, signaling price pressure despite improving demand. These trends highlight how Airbnb occupancy rates by country—or even by city—must be interpreted alongside metrics like average daily rate (ADR) and supply growth to gauge true market health.

For operators, the takeaway is clear: city-level data often provides more actionable insights than broad national figures. A 47% occupancy rate in Guatemala City, for instance, may reflect a different demand profile than the 44% recorded in Sharjah, where lower ADRs ($25 vs. $39) suggest distinct guest segments and competitive dynamics. Property managers and investors must therefore tailor strategies to local conditions, whether optimizing pricing in high-occupancy markets like Prague or addressing supply saturation in destinations like Bali.

Methodological nuances and their business implications

AirDNA’s methodology defines occupancy as the share of available nights booked across active listings over a 12-month period. This approach captures real demand but also makes the metric sensitive to supply fluctuations. A stable or rising Airbnb occupancy rate by country can coexist with revenue declines if inventory growth outpaces demand or if ADR weakens—a pattern observed in Bali’s recent performance. For revenue management systems and property management software (PMS) providers, this underscores the need to integrate occupancy data with dynamic pricing tools and supply-side analytics to help operators navigate such complexities.

Regulators and local authorities also monitor these trends, though their focus often extends beyond raw occupancy. In Lisbon, for example, the 2.6% year-over-year decline may factor into debates over housing affordability or tourism taxation, while Prague’s 64% occupancy could inform discussions about licensing caps or seasonal restrictions. For industry stakeholders, understanding these policy contexts is as critical as tracking the metrics themselves.

Strategic considerations for short-term rental professionals

The current data landscape presents both challenges and opportunities for the sector. While country-level Airbnb occupancy rates by country remain elusive, the available city benchmarks offer a foundation for targeted decision-making. Operators in high-occupancy markets like Oslo or Lisbon may prioritize guest experience enhancements to justify premium pricing, while those in lower-occupancy regions like Sharjah or Guatemala City might explore niche marketing strategies or partnerships with local tourism boards to stimulate demand.

For software vendors and service providers, the fragmentation of data highlights a growing need for tools that aggregate and contextualize performance metrics across geographies. Platforms that can correlate occupancy trends with external factors—such as economic indicators, event calendars, or regulatory changes—will be particularly valuable to property managers seeking to optimize their portfolios. Meanwhile, investors evaluating cross-border opportunities should complement occupancy data with on-the-ground due diligence, as national averages often obscure hyperlocal risks and opportunities.

Ultimately, the most reliable insights emerge from combining granular data with a nuanced understanding of market dynamics. As the short-term rental industry matures, professionals who leverage both quantitative benchmarks and qualitative context will be best positioned to adapt to evolving demand patterns and regulatory landscapes.

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