Booking report
Last updated
Last updated
The booking report function generates a .csv file containing a comprehensive list of users who have made reservations for a resource within a specific building or floor, over a designated date range. The report also details resource occupancy and environmental ranges for the specific bookings (where relevant sensor data is available).
Once the report is ready, you will receive a notification email indicating that it is available for download. The email will include a link for you to retrieve the .csv file onto your device.
To initiate the report, locate the global print icon situated in the top row next to your account profile, and select booking report.
Upon clicking, a pop-up window will appear, allowing you to specify a building, floor, and date range. The building field is obligatory, and you have the option to further narrow down to a specific floor within that building.
Please note that the date range is limited to one month of data due to the potential volume of records that could be generated.
Once you have defined your parameters, click on generate. You will receive a notification confirming that your report is being processed and will be sent to you once it's ready.
The resulting .csv file will contain the following columns:
Created date / time
Organiser
Organiser email
Resource name
Resource type
Building
Floor
Start date / time
End date / time
Duration
Number of attendees
Planned / ad hoc
Checked in
Average occupancy (during booking time period)
Max occupancy (during booking time period)
Average temperature (during booking time period)
Average air quality (during booking time period)
Average humidity (during booking time period)
Average co2 (during booking time period)
Average PM (during booking time period)
Average sound level (during booking time period)
Average ambient noise (during booking time period)
Energy consumed (during booking time period)
Once downloaded, you will have the flexibility to manipulate the data in the .csv file to suit your needs.
For example, you may want to analyse the most frequently utilised time slots for resource bookings in order to optimise scheduling for in-room maintenance.
