Live Stream Reporting
Overview
During a live stream, you have reporting on the number of unique views for the current stream via the CrowdComms dashboard (CMS). More detailed reporting is provided post event. The post event stream report includes breakdown of all streams including who watched by users first & last name.
Please note:
- All available analytics and reports are outlined within this Analytics and Reporting section.
- This data is not available in the CMS. Your livestream report will be provided within 48 hours post-event.
- Data included in the stream report that identifies the user includes first name and last name.
- If you need to analyse further user data such as group or custom fields, this can be achieved by cross referencing the reports available and the people export.
The Stream Report Explained:
Summary Tab
This provides a summary of all streams in one place. Here you can see the number of views and watch times on each stream as a whole. You can also see the split of live vs on demand views. This is a really useful tab to use to drill down on your data. The various columns can be looked at as follows:
Please note: Stats for pre-recorded videos hosted externally will work in the same way, as long as they were streamed via MUX as if live. For any videos housed in a live stream window but hosted externally such as vimeo, the system won’t be able to distinguish between live and on demand views and so all views will show as ‘live views’.
All Streams Combined
This is similar to the summary tab, but rather than just having a numerical value for each session, you can see the views by user.
Individual Stream Stats
Here you will see the exact same data as in the ‘all streams combined’ tab, in the exact same format. This may be more useful if you have lots of streams and want to view them broken down.
Please note: For both individual stream pages and all streams combined data, users may appear in the list more than once. Within the data for each session/stream, you will have one line per user per day. i.e If somebody watched the same session on two separate days, then there would be two data sets for that user within that one stream. If you want to see unique views only, then you will need to apply a filter.