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Bookings Topic

Michael Gimingham avatar
Written by Michael Gimingham
Updated over 2 weeks ago

What is the Bookings Dataset?

The Bookings dataset provides detailed, reservation-level data directly from your property management system (PMS). This powerful dataset gives you granular insights into stay patterns, booking behavior, and revenue performance across your properties. It serves as the foundation for understanding your current business performance as well as historical trends.

Key Information Available in the Bookings Dataset

The Bookings dataset allows you to analyze:

  • Occupancy and Revenue Performance: Track Units, ADR, Revenue, RevPAR, and other key metrics

  • Guest Stay Patterns: Analyze Length of Stay and Lead Time trends

  • Segment Performance: Compare business mix across different market segments

  • Channel Production: Evaluate booking channel effectiveness and profitability

  • Period-over-Period Analysis: Compare current performance to historical benchmarks (STLP or Previous)

Core KPIs Explained

  • Units: The number of room nights sold during a specific period

  • ADR (Average Daily Rate): The average rate per occupied room

  • Accommodation Revenue: The total rooms revenue generated

  • RevPAR (Revenue Per Available Room): Total rooms revenue divided by total available rooms

  • Occupancy: The percentage of available rooms that were sold

Period-over-Period Analysis

Every KPI in the Bookings dataset has three variants to help you assess performance trends:

  1. Base Measure (e.g., "ADR"): Current on-the-books performance

  2. STLP Measure (e.g., "ADR STLP"): Same Time Last Period - shows how the metric was performing at the same point in time in your comparison period

  3. Previous Measure (e.g., "ADR Previous"): Shows the final actualized value from your comparison period

Common Ways to Use the Bookings Dataset

Daily Performance Tracking

  • Monitor daily Units, ADR, and Revenue performance

  • Compare current performance to previous periods

  • Identify days requiring revenue management attention

Business Mix Analysis

  • Break down performance by segment, channel, or rate plan

  • Identify high-value segments or channels

  • Target marketing efforts based on performance data

Booking Behavior Analysis

  • Track lead time and length of stay trends

  • Identify shifts in guest booking patterns

  • Adjust pricing and distribution strategies accordingly

Profitability Assessment

  • Analyze revenue net of commission costs

  • Evaluate channel cost efficiency

  • Make informed distribution decisions

Advanced Analysis Tips

  • Combine Multiple Dimensions: Add multiple dimensions like segment, channel, and rate plan to understand performance drivers

  • Use Day-Type Analysis: Compare weekday vs. weekend performance patterns

  • Track Geographical Source Markets: Analyze guest country of origin to inform marketing strategies

  • Monitor Lead Time Changes: Watch for shifts in booking window to adjust pricing strategies

Need More Help?

For more guidance or specific inquiries about integrating and leveraging this data, please refer to the Insights help documentation or reach out to our Advisory team for personalized support.

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