What is Youtube Analytics

Definition:

Youtube Analytics Youtube Analytics is the tool for analysing user activity and the performance of Youtube videos. Implemented in 2011 to replace Youtube Insights, it is a very complete platform, with multiple functionalities and that is receiving important updates frequently, the last being the most important in 2018.

Why use Youtube Analytics

It is important not to ignore the multiple utilities offered by Youtube Analytics. It is long the most complete analysis tool of this platform and essential if we want to improve the performance of our channel. Thanks to Youtube Analytics we can know how our audience is segmented and in this way design videos more to their measure, see which of your content is being positioned, find out the sources of traffic and better organize your channel.

What Youtube Analytics offers

The latest update to Youtube Analytics has greatly changed the way information is presented. Currently, we have 4 tabs each of which presents a specific type of data:

  • Overview:In this section we can see a general summary about the most important things that affect our account. Here are the graphs of views (minutes and total views), the evolution of the number of subscribers, your main videos in the period you determine, and information about the most recent activity.
  • Reach viewers:Here we can get all kinds of information about how viewers reach your channel. This tab includes the number of impressions and click-through rate, number of views and unique viewers, the traffic sources from which viewers reach your videos, both internal and external, and the keywords that users enter to search for you.
  • Viewer interest:This tab contains everything about how viewers behave once within your channel, including average viewing time, which tabs click at the end of your videos, and clicks on cards you’ve added.
  • Grow your audience:The latest set of data offered by Analytics is intended to increase the number of followers of your videos. Basically this is where we find broken down the segmented profile of our users by sex, age, geographical area, etc …

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