Help Center Insights

Analytics & Reports

Understanding your booking metrics

The Analytics page gives you insights into booking trends, capacity utilisation, and customer behaviour.

Location: Sidebar > Analytics


Date Range Selection

Choose the period you want to analyse:

Quick Presets

  • 7 days — Last week snapshot
  • 14 days — Two-week trend
  • 30 days — Monthly overview
  • 90 days — Quarterly view

Report Periods

  • This Month / Last Month
  • This Quarter / Last Quarter
  • This Year / Last Year

Resource Filter

Filter all metrics to a specific resource, or view all resources combined.


KPI Cards

Six key performance indicators shown at the top:

Total Bookings

The number of confirmed bookings in the period. Includes customer bookings and staff blocks.

Total Participants

The sum of all party sizes — how many individual people were booked. A booking for a family of 4 counts as 4 participants.

Occupancy Rate

Formula: Consumed capacity / Total available capacity

How full your timeslots are on average. An occupancy rate of 75% means three-quarters of your available slots are being used.

  • Below 50% — Room to grow. Consider marketing or reducing capacity to create urgency.
  • 50–80% — Healthy utilisation.
  • Above 80% — Great demand. Consider adding capacity or raising prices.

Check-in Rate

Formula: Checked-in bookings / Total confirmed bookings

What percentage of booked customers actually showed up. Low check-in rates might indicate:

  • No-show problems (consider stronger cancellation policies)
  • Customers booking “just in case” (consider booking limits)
  • Staff not consistently checking people in

Cancellation Rate

Formula: Cancelled bookings / Total bookings (including cancelled)

How many bookings were cancelled. Some cancellation is normal, but high rates might suggest:

  • Customers booking too far in advance
  • Pricing issues
  • Weather sensitivity (outdoor venues)

Hold Conversion Rate

Formula: Holds that became confirmed bookings / Total holds created

How many customers who started the booking process actually completed it. Low conversion might indicate:

  • Checkout flow issues
  • Price shock at the payment step
  • Technical problems with the widget

Charts

Bookings Over Time

Area chart showing daily booking and participant counts. Use this to spot:

  • Day-of-week patterns (weekends vs. weekdays)
  • Growth trends
  • Seasonal changes

Capacity Utilisation

Area chart comparing available capacity vs. consumed capacity over time. The gap between the lines shows unused capacity.

Member vs. Public

Percentage breakdown of member pool vs. public pool bookings. Helps you understand:

  • Whether member capacity allocation is right-sized
  • Trends in membership adoption
  • If pool release is working effectively

By Day of Week

Bar chart showing booking distribution across weekdays. Identifies:

  • Your busiest days
  • Under-utilised days (opportunity for promotions)
  • Staffing alignment

Peak Hours

Bar chart showing occupancy percentage by hour of day. Identifies:

  • Your peak hours (consider premium pricing)
  • Off-peak hours (consider discounts)
  • Staffing needs throughout the day

Tables

By Resource

Breakdown per resource showing:

  • Booking count
  • Rider count
  • Total capacity (sum of all timeslot capacity)
  • Consumed capacity
  • Occupancy rate %

Daily Breakdown by Resource

Detailed matrix showing daily stats per resource. Useful for granular analysis and spotting day-level issues.


CSV Export

Export your data for further analysis. Available exports:

ExportContents
SummaryKPI overview for the period
DailyDay-by-day metrics
By ResourceResource-level breakdown
DetailedIndividual booking records
Full ReportAll of the above combined

Exports are CSV format, compatible with Excel, Google Sheets, and other spreadsheet tools.


Tips

  • Check weekly: Review the 7-day view at least once a week to spot trends
  • Compare periods: Use “This Month vs Last Month” to track growth
  • Watch occupancy: If consistently above 80%, consider expanding capacity
  • Monitor conversion: A drop in hold conversion rate often indicates a technical issue
  • Export monthly: Keep CSV exports for year-over-year comparisons
  • Filter by resource: If you have multiple resources, analyse each one separately — they may have very different patterns

What’s Next?