Users Reservations Trend
This page provides user-level insights into reservation data.
Last updated
Was this helpful?
This page provides user-level insights into reservation data.
Last updated
Was this helpful?
The charts display the top or bottom N users or teams based on their highest reservation counts which is categorised by resource type.
Identify power users and teams, optimise booking policies.
Detect underutilisation by tracking low-usage users and teams.
Improve resource allocation by analysing frequent usage trends.
The charts display the top or bottom N users and teams ranked by their total reservation duration (in days), categorised by resource type.
Identify users and teams occupying resources for extended periods.
Optimise resource allocation by balancing long and short reservations.
Improve booking policies by detecting users and teams who overuse resources.
The charts display the top or bottom N users and teams based on their highest reservation counts, categorised into morning, afternoon, and all-day time periods.
Identify peak booking times for different users and teams.
Optimise resource availability by time of day.
Detect underutilisation trends in specific time slots.
The charts display the top or bottom N users and teams with the highest number of no-show reservations. No-show reservations refer to bookings where a user or team reserved a resource but did not utilise it. It is linked to a sensor, which identifies reservations as no-shows if the reserved resource is not detected.
Identify users or teams who frequently book but do not show up.
Improve resource availability by reducing no-show rates.
Implement automated cancellation policies for repeated no-shows.
The KPI cards display individual user or team metrics. When a user or team is selected from the filter, the KPI cards update accordingly.
Monitor individual user or team activity for booking trends.
The summary table displays the raw data for all bookings made by users within the selected time range. This data is used to create the above charts. Users can download the data as a CSV file or create their own charts from the summary table.
Allows users to export data for further analysis or reporting.
