The Booking Patterns dashboard helps you understand when and where your resources are most booked and generate the highest revenue. Use it to identify peak time slots, analyze trends by location and resource type, and uncover opportunities to optimize pricing and maximize revenue.
Right-click any value in the charts to drill down and view its details at the transaction level.
Before you start
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Dashboard overview
The widgets at the top of the dashboard show summarized insights about bookings at your organization during the selected timeframe:
Total Bookings – The total number of bookings in the selected period.
Booked Hours – The total number of hours booked in the selected period.
Bookings Revenue – The total revenue generated from bookings in the selected timeframe.
Peak Month – The month in the selected timeframe with the highest total booked hours.
Peak Day – The day of the week in the selected timeframe with the highest total booked hours (not limited to the peak month).
Peak Time Slot – The time of day with the highest total booked hours across the selected timeframe (not limited to the peak day and month).
Cross-reading tip (volume vs. revenue)
Compare Booked Hours surfaces (Section 1) with Revenue surfaces (Section 2):
Low hours + low revenue in the same bands → utilization is thin (room to add volume).
High revenue + neutral or low hours → higher Rate relative to volume.
High hours + neutral or low revenue → lower Rate relative to volume.
Line charts
The line charts on the dashboard display booking duration and revenue metrics, broken down by month of the year and day of the week.
Green areas indicate high-performing periods where revenue can be maximized, while pink areas may suggest low demand, in which case promotional pricing could increase bookings.
Average Weekly Booked Hours by Month
What it shows: Average booked hours per week for each month of the year within the selected timeframe (seasonality of volume).
How to read: Points above or below the long-run average indicate months with systematically higher or lower sold hours.
Optimization potential signal: Months persistently below average suggest utilization headroom; months above average suggest capacity pressure, where rate realization tends to be stronger.
Average Daily Booked Hours by Day of Week
What it shows: Average booked hours per day for each day of the week in the selected timeframe (weekly volume shape).
How to read: Reveals which weekdays regularly accumulate more or fewer sold hours.
Optimization potential signal: Weekdays with consistently low booked hours indicate underfilled days; those with very high booked hours indicate tight inventory windows.
Average Weekly Bookings Revenue by Month
What it shows: Average weekly revenue generated from bookings for each month of the year in the selected timeframe (seasonality of revenue).
How to read: Deviations from the average band show months that consistently over- or underperform revenue-wise.
Optimization potential signal: Sustained negative deviations indicate revenue under-realisation; positive deviations indicate strong pricing power in those months.
Average Daily Bookings Revenue by Day of Week
What it shows: Average daily revenue generated from bookings for each day of the week in the selected timeframe (seasonality of revenue).
How to read: Deviations from the average band show months that consistently over- or underperform revenue-wise.
Optimization potential signal: Sustained negative deviations indicate revenue under-realisation; positive deviations indicate strong pricing power in those months.
Heatmaps
The heatmaps on the dashboard show the total booked hours and total prorated revenue amount from bookings per day of the week and hour of the day. You can use these heatmaps to quickly identify underutilized hours or high-demand periods that may benefit from price adjustments or targeted promotions.
Values above average are highlighted in green, while ones below average are colored in pink.
Total Booked Hours by Month and Day of Week
This heatmap displays the total booked hours for each day of the week per month in the selected timeframe.
Total Bookings Revenue by Month and Day of Week
What it shows: Total booking revenue for each day of the week per month within the selected timeframe (structural volume patterns).
How to read: Column consistency = stable weekday effect; row shifts = seasonal effects across all weekdays.
Optimization potential signal: Persistent lows or highs by month–weekday highlight durable utilisation gaps or sustained pressure worth monitoring when adjusting rates.
Total Booked Hours by Day of Week and Hour of Day
What it shows: Total booked hours for each day of the week and hour of the day in the selected timeframe (intra-day volume distribution).
How to read: Contiguous green blocks = concentrated sold time; red blocks = systematically thin windows.
Optimization potential signal: Red clusters mark quiet hour bands with utilization headroom; green clusters indicate constrained bands where price tends to be higher.
Total Bookings Revenue by Day of Week and Hour of Day
What it shows: Total booking revenue for each day of the week and hour of the day within the selected timeframe (intra-day revenue distribution).
How to read: Look for contiguous green or red blocks (sustained strong or weak bands) and compare the same hour across weekdays to see differences.
Optimization potential signal: Green clusters mark bands where revenue realisation is strong; red clusters mark bands with relative headroom; shoulders around green blocks often indicate transition zones.
