Analytics explained

Note that all data is collected anonymously and no personal data is stored within GoBright Analytics.

GoBright measures the occupancy of rooms and desks and can be viewed in the ‘Analytics’ menu options. This gives insights into whether rooms and desks are used efficiently and whether the occupancy rate can be improved.

Log in to the GoBright portal with your manager account, and choose Analytics > Occupancy.

Metrics

The occupancy report gives you insight into the occupancy rates, measured by different metrics.

The metrics are shown as occupancy percentages, calculated as a percentage of the total available time, where the total available time is 08:30-17:00 by default, but can be selected to fit your situation.

Depending on your licensing and hardware, the following metrics are available:

• Bookings: the occupancy percentage of reservations that have been made. This shows bookings that have been made on bookable spaces.
  Non-bookable spaces are not included, as there are no bookings on those spaces.
• No-shows: the occupancy percentage of the time that a space was booked, but no one showed up.
  So if a space was booked from 08:30-17:00 and this becomes a no-show, this will result in a no-show occupancy percentage of 100% for that space on that day (assuming the default opening times of 08:30-17:00 are used).
  In general, this metric gives you insight into how well there is lived up to bookings that are made.
• Detected occupations: the occupancy percentage based on actual occupancy as measured by the occupancy sensors.
• Check-ins at Connect: the occupancy percentage of the checked-in time, that users are checked-in via the GoBright Connect device on non-bookable desks.

Report type

First, select the report type to view data on a daily or hourly basis.
Daily will show the data per day, and hourly per hour over the selected period. The hourly report will give you the ability to see which hours are peak hours.

Location & period

Choose the location where occupancy has been measured, this can be set from all locations to a single room or desk. The date needs to select which period has to be included in the analysis.

Time

The time plays an important part in the data that is being displayed. The time chosen is used as the maximum occupancy time, so the chosen time is the definition of 100%.

Example 1 ‘Company A’:

Company A has opening hours each Monday till Friday from 08:30 to 17:00.
When Company A filters its data using the settings above it will need to set the time between 08:30 and 17:00 and use the ‘working days only’ checkbox.

If Company A would set their time between 08:00 and 17:00, the 100% occupancy is only reached for e.g. bookings that start (or before) 08:00, and end at 17:00 (or later). As this would normally not happen, this will in general result in lower occupancy percentages.

Example 2 ‘Company B’:

Company B has opening hours each Monday till Sunday from 08:00 to 20:00. Company B will need to set the time between 08:00 and 20:00 but does not necessarily have to use the ‘working days only’ checkbox.

If Company B would set their time between 08:00 and 17:00, they would effectively not display data from the last three hours of each day. In this case, it’s possible to achieve a 100% ‘Booking’ occupancy rate easily, but however that data is inaccurate because opening hours are longer than taken into account.

Filters

When analyzing several spaces at once (e.g. a whole building), you should only compare the metrics against each other, when the include the same amount and type of spaces.

For example:
All your spaces are fitted with occupancy sensors but have a mix of spaces that are bookable and that are non-bookable.
When you take the data of all these spaces into a single graph, you should not compare the bookings percentage and occupancy percentages. This is because the bookings percentage are only measured for the bookable spaces, and the actual usage is measured for all the spaces (bookable and non-bookable).

Therefore you can utilize the ‘select spaces with’ filter, in this case, you can check the box ‘bookings’ to only include the spaces that are bookable. Now the graph will include bookable spaces for all the metrics, making the data comparable.

More ways to view data

There are two more ways to view the data that GoBright has collected:

Display the top 10 occupations

Log in to the GoBright portal with your manager account, and choose Analytics > Occupations top 10.

This displays an overview of the most and least booked rooms and desks. The same filters apply as the occupancy tab. The top 10 can be based either on bookings or on actual usage (sensor data), which gives you a quick insight into the most popular and least popular spaces.

Display no-shows

Log in to the GoBright portal with your manager account, and choose Analytics > No-shows.

This displays an overview of organizers who made a booking and shows a percentage of time that the room or desk has not been used. This gives insight when organizers take too much time and waste part of their reservation by not being in the room.