Vacation Rental Performance KPIs | Global OTA Data | Property-Level KPIs with Revenue & Occupancy Insights

--- DATASET OVERVIEW --- This dataset captures detailed performance data for individual vacation rental properties, providing a complete picture of operational success metrics across different timeframes and market conditions. With weekly updates and four years of historical data, it enables both point-in-time analysis and long-term trend identification for property-level performance. The data is derived from OTA platforms using advanced methodologies that capture listing, calendar and quote details. Our algorithms process this raw information to produce standardized and enriched performance metrics that facilitate accurate comparison across different property types, locations, and time periods. By leveraging our other datasets and machine learning models, we are able to accurately detect guest bookings, revenue generation, and occupancy patterns. --- KEY DATA ELEMENTS --- Our dataset includes the following core performance metrics for each property: - Property Identifiers: Unique identifiers for each property with OTA-specific IDs - Geographic Information: Location data including neighborhood, city, region, and country - Property Characteristics: Property type, bedroom count, bathroom count, and capacity - Occupancy Metrics: Daily, weekly, and monthly occupancy rates based on actual bookings - Revenue Generation: Total revenue, average daily rate (ADR), and revenue per available day (RevPAR) - Booking Patterns: Lead time distribution, length of stay patterns, and booking frequency - Seasonality Indicators: Performance variations across seasons, months, and days of week - Competitive Positioning: Performance relative to similar properties in the same market - Historical and Forward Looking Trends: Year-over-year and month-over-month performance changes --- USE CASES --- Property Performance Optimization: Property managers can leverage this dataset to evaluate the performance of individual listings against market benchmarks. By identifying properties that underperform relative to similar listings in the same area, managers can implement targeted improvements to pricing strategies, property amenities, or marketing approaches. The granular performance data enables precise identification of specific improvement opportunities at the individual property level. Competitive Benchmarking: Property owners and managers can benchmark their listings against competitors with similar characteristics in the same market. The property-level performance metrics enable detailed comparison of occupancy rates, ADR, and revenue generation across comparable properties. This competitive intelligence helps identify realistic performance targets and market positioning opportunities. Portfolio Optimization: Vacation rental portfolio managers can analyze performance variations across different property types and locations to optimize investment and management decisions. The dataset supports identification of high-performing property configurations and locations, enabling strategic portfolio development based on actual performance data rather than assumptions. Seasonal Strategy Development: The historical performance data across different seasons enables development of targeted seasonal strategies. Property managers can analyze how different property types perform during specific seasons or events, informing marketing focus, pricing adjustments, and operational planning throughout the year. Performance Forecasting: Historical performance patterns can be leveraged to develop accurate forecasts for future periods. By analyzing year-over-year trends and seasonal patterns, property managers can anticipate performance expectations and set realistic targets for occupancy and revenue generation. --- ADDITIONAL DATASET INFORMATION --- Delivery Details: • Delivery Frequency: daily | weekly | monthly | quarterly | annually • Delivery Method: scheduled file loads • File Formats: csv | parquet • Large File Format: partitioned parquet • Delivery Channels: Google Cloud | Amazon S3 | Azure Blob • Data Refreshes: daily Dataset Options: • Coverage: Global (most countries) • Historic Data: Available (2021 for most areas) • Future Looking Data: Available (Current date + 180 days+) • Point-in-Time: Available (with weekly as of dates) • Aggregation and Filtering Options: • Area/Market • Time Scales (daily, weekly, monthly) • Listing Source • Property Characteristics (property types, bedroom counts, amenities, etc.) • Management Practices (professionally managed, by owner) Contact us to learn about all options. --- DATA QUALITY AND PROCESSING --- Our data processing methodology ensures high-quality, reliable performance metrics that accurately represent actual property performance. The raw booking and revenue data undergoes extensive validation and normalization processes to address inconsistencies, identify anomalies, and ensure comparability across different property types and markets. We employ sophisticated algorithms to standardize performance metrics across different OTA platforms, accounting for variations in reporting methodologies and data structures. This harmonization process ensures that users receive consistent, comparable metrics regardless of the original listing platform. Regular quality assurance processes verify data accuracy, completeness, and consistency, ensuring that users receive reliable information for critical business decisions. Our comprehensive coverage across major global markets provides a truly representative view of vacation rental performance at the property level.