Live stream traffic analytics is a powerful tool to give you insights about who visited the stream, how many times they viewed it, and the time span spent watching the live stream.
This data will be available from the moment participants visit the Streams page on your Brella event. You can export stream traffic data per stream or all together at once at any time. You will receive three files which include, visitors, interactions, and activity.
Export data per stream
Navigate to the Admin Panel - Content
Click on Streams.
And then click on Analytics.
There scroll down and click on Export (.csv). The data is exported in CSV format.
Export all stream traffic data
Navigate to the Admin Panel - Content
Click on Streams.
Select Settings,
Under Export stream traffic data - click on Export zip.
You will receive three separate files:
a. Stream name visitors.csv - includes all the total interactions per visitor.
* This file will show interactions done since the event creation and post-event.
b. Stream name interactions. csv - includes all the visitors' interactions combined.
* This file will show interactions done since the event creation and post-event.
c. Stream name activity. csv - includes all the visitors' activity with the stream.
* This file will only show event dates and will start tracking activity as soon as a participant watches the streams.
💡 *The average viewer is probably the closest measure of actual attendance at any given point. It is calculated by dividing the Total Watch Time by all watchers on the interval duration (15 minutes). So, if two people watch half of the interval, you get one average viewer. For example, suppose Peter watched the first half and Patrick watched the second half. In that case, the amount of viewers at any given point is 1, while if they both only watched the first half, the attendance would first be two and then 0 for the second half of the interval, also averaging 1.
Another example: If you see that on your results are average viewers are 2.66, it could mean that two people watched the entire 15-minute interval and a third person watched for 10 minutes, or there were more viewers (the unique viewer count), but they didn’t stick so long.
⭐ Tip: To understand the stream and session traffic data definitions please visit this article.