The VR Direct Rates dataset offers a comprehensive and up-to-date view of vacation rental pricing and availability, sourced directly from property management systems.

With strong coverage in North America and limited global data, this dataset provides granular, unit-level information on rates, occupancy, and property characteristics.

Updated daily, it enables real-time analysis of pricing strategies, demand patterns, and market trends across various locations and property types.

This dataset is an invaluable resource for revenue managers, market analysts, and investors in the vacation rental industry, facilitating data-driven decision-making in pricing, investment, and competitive positioning

--- DATASET OVERVIEW --- This dataset captures detailed information about each vacation rental property listing, providing insights that help users understand property distribution, characteristics, management styles, and guest preferences across different regions. With extensive global coverage and regular weekly updates, this dataset offers in-depth snapshots of vacation rental supply traits at scale.

The data is sourced directly from major OTA platforms using advanced data collection methodologies that ensure high accuracy and reliability. Each property listing is tracked over time, enabling users to observe changes in supply, amenity offerings, and host practices.

--- 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 - Listing Characteristics: Property type, bedroom count, bathroom count, in-service dates. - Amenity Inventory: Comprehensive list of available amenities, including essential facilities, luxury features, and safety equipment. - Host Information: Host details, host types, superhost status, and portfolio size - Guest Reviews: Review counts, average ratings, detailed category ratings (cleanliness, communication, etc.), and review timestamps - Property Rules: House rules, minimum stay requirements, cancellation policies, and check-in/check-out procedures

--- USE CASES --- Market Research and Competitive Analysis: VR professionals and market analysts can use this dataset to conduct detailed analyses of vacation rental supply across different markets. The data enables identification of property distribution patterns, amenity trends, pricing strategies, and host behaviors. This information provides critical insights for understanding market dynamics, competitive positioning, and emerging trends in the short-term rental sector.

Property Management Optimization: Property managers can leverage this dataset to benchmark their properties against competitors in the same geographic area. By analyzing listing characteristics, amenity offerings and guest reviews of similar properties, managers can identify optimization opportunities for their own portfolio. The dataset helps identify competitive advantages, potential service gaps, and management optimization strategies to improve property performance.

Investment Decision Support: Real estate investors focused on the vacation rental sector can utilize this dataset to identify investment opportunities in specific markets. The property-level data provides insights into high-performing property types, optimal locations, and amenity configurations that drive guest satisfaction and revenue. This information enables data-driven investment decisions based on actual market performance rather than anecdotal evidence.

Academic and Policy Research: Researchers studying the impact of short-term rentals on housing markets, urban development, and tourism trends can use this dataset to conduct quantitative analyses. The comprehensive data supports research on property distribution patterns and the relationship between short-term rentals and housing affordability in different markets.

Travel Industry Analysis: Travel industry analysts can leverage this dataset to understand accommodation trends, property traits, and supply and demand across different destinations. This information provides context for broader tourism analysis and helps identify connections between vacation rental supply and destination popularity.

--- ADDITIONAL DATASET INFORMATION --- Delivery Details: • Delivery Frequency: 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: weekly

Dataset Options: • Coverage: Global (most countries) • Historic Data: N/A • Future Looking Data: N/A • Point-in-Time: N/A • Aggregation and Filtering Options: • Area/Market • Time Scales (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 collection and processing methodology ensures high-quality data with comprehensive coverage of the vacation rental market. Regular quality assurance processes verify data accuracy, completeness, and consistency.

The dataset undergoes continuous enhancement through advanced data enrichment techniques, including property categorization, geographic normalization, and time series alignment. This processing ensures that users receive clean, structured data ready for immediate analysis without extensive preprocess...

Comprehensive global lodging intelligence covering more than seven million hotel and short-term rental properties worldwide.

The Complete Lodging Dataset provides a full-market view of the global accommodation landscape by integrating data from hotel reservation systems, Online Travel Agencies (OTAs), and directly connected property management systems. It includes verified property identifiers, occupancy rates, ADR, RevPAR, pricing trends, and physical attributes across both traditional hotel inventory and short-term rental supply.

Sourced from real booking and reservation data and refined through proprietary normalization processes, this dataset ensures consistency and accuracy across all lodging types. Updated on a frequent cadence, it enables robust benchmarking, forecasting, and investment analysis across countries, cities, and submarkets.

Key Highlights: Extensive Global Coverage: More than 7 million verified hotel and short-term rental properties across 200+ countries.

Unified Market View: Combines professional rental data, OTA listings, and hotel system performance for complete supply visibility.

Comprehensive Metrics: Includes occupancy, ADR, RevPAR, booking patterns, and property-level attributes.

Standardized Data Structure: Harmonized schema for cross-market and cross-segment analysis.

Flexible Delivery: Available via secure API or downloadable datasets with customizable geography and temporal depth.

Use It To: Analyze total lodging supply and demand across regions and property types.

Benchmark market performance between hotels and short-term rentals.

Support tourism, development, and investment strategies with unified lodging insights.

Integrate verified, cross-channel performance data into valuation, forecasting, and economic models.

What are the top vacation rentals in Cold Spring Harbor? How many vacation rentals have private pools in Cold Spring Harbor? Which vacation homes in Cold Spring Harbor are best for families? How many Rentbyowner vacation rentals are available in Cold Spring Harbor?

--- DATASET OVERVIEW --- This dataset delivers critical market intelligence including occupancy rates, average daily rates, revenue per available rental, booking pace, and seasonal demand patterns across different geographic areas. With daily updates, AI-driven forward projections, and four years of historical data, it offers property managers, investors, and market analysts the essential benchmarks needed to understand market performance, identify emerging trends, and develop data-driven strategies in the rapidly evolving vacation rental sector.

The data is sourced from major OTA platforms and processed through advanced aggregation methodologies that ensure statistical validity while preserving crucial market signals. Our proprietary algorithms enhance the raw data with sophisticated trend analysis and forward-looking projections, enabling users to anticipate future market conditions with increased confidence.

--- KEY DATA ELEMENTS --- Our dataset includes the following core performance metrics for each property: - Property Groups: Group by property type, bedroom counts, key amenities groups - Geographic Identifiers: Multiple geographic levels (vacation area, vacation region, county, etc) - Temporal Dimensions: Daily, weekly, monthly, and quarterly performance metrics - Occupancy Metrics: Market-wide occupancy rates and booking pace indicators - Pricing Metrics: Average daily rates (ADR), revenue per available rental night (RevPAR), and price trends - Booking Pattern Indicators: Average lead time, length of stay, and booking frequency - Seasonality Metrics: Seasonal demand patterns and year-over-year comparisons - Demand Forecasts: Forward-looking projections for occupancy and pricing trends - Historical Pacing: Snapshots into how stay date ranges developed for tracking pacing trends - Forward Looking Trends: Area KPIs 180-365 days into the future

--- USE CASES --- Market Performance Benchmarking: Property managers and owners can benchmark their individual property or portfolio performance against market-wide metrics. By comparing property-specific occupancy rates, ADR, and RevPAR against market averages for similar property types, managers can assess relative performance and identify areas for improvement. These benchmarks provide crucial context for performance evaluation and goal setting.

Investment Decision Support: Real estate investors and portfolio managers can use market-level performance data to identify attractive investment opportunities across different geographic areas. The comprehensive market metrics reveal high-performing areas, emerging markets, and potential investment risks based on actual performance data rather than anecdotal evidence. This information supports data-driven acquisition strategies and portfolio diversification decisions.

Demand Forecasting and Planning: Revenue managers and property operators can leverage the historical performance patterns and forward-looking projections to anticipate demand fluctuations and plan accordingly. The seasonal patterns, booking pace indicators, and AI-enhanced forecasts enable proactive rate adjustments, marketing timing, and operational planning to maximize revenue opportunities during high-demand periods.

Market Entry Analysis: Companies considering entering new vacation rental markets can utilize this dataset to understand market dynamics, competitive intensity, and performance expectations before committing resources. The comprehensive market metrics reduce market entry risk by providing clear visibility into potential revenue opportunities, seasonal patterns, and overall market health.

Performance Attribution Analysis: Market analysts can use this dataset to understand the drivers behind performance variations across different markets and time periods. By analyzing how market composition, seasonality, and external factors influence overall performance, analysts can identify the underlying causes of performance trends and develop more accurate forecasting models.

Economic Impact Assessment: Economic development organizations and tourism authorities can leverage this dataset to quantify the economic contribution of the vacation rental sector. The market-wide revenue metrics, occupancy patterns, and supply growth indicators provide valuable inputs for economic impact studies and policy development related to the short-term rental industry.

--- 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 + 180-365 days) • Point-in-Time: Available (with weekly as of dates) • Aggregation and Filtering Options: • Area/Market ...

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