Videos are playing an increasingly central role in the digital evolution, for this reason it is very important to have a system of analytics which is able to provide a detailed report on their use. ShinyStat Video Analytics allows, among other functions, to aggregate their videos according to categories.
With our tool, enabling the management of the categories of video, infact, it’ s possible to analyze the complex areas of interest of its users and understand their browsing behavior.

ShinyStat Video Analytics - EPC & CF

Through the CF (category force) report, present on the “Categories Correlation” section, you can see very clearly the power of attraction that a single channel exerts on the audience. The category force, in fact, shows the percentage by which the category in question was seen first, and, in consequence, the ability to catch external visitors.

In this case, you may notice that the video section “Space & Astronomy”  is the one that has had more grip on an external audience, while on “Earth and Environment” has attracted less public.

In addition to this, there is another very interesting metric, as indicated in the report with the name of ECP, external correlation percentage. The ECP indicates, through the analysis of the historical stats, the users’ percentage  that visit another channel in the same video session.

Following our example above, the audience who watched the video for “Space & Astronomy”, after logging into this channel, visited another in 7.95% of cases, while only 1, 45% users who looked at the video for “Earth and Environment” was also interested in other video categories .

ShinyStat Video Analytics - IPC

Clicking on the category will appear another report, very significant on the steps that take place between the various channels.
For example, under “Space & Astronomy”, we can analyze that the 7.95% of users also viewed other categories, is so divided: 85, 71% viewed the video for “Space Missions “, while 14.29% of” Earth and Environment “.

The PCI, however, indicates the Internal Correlation Percentage, that is the percentage of users who have only watched that category and no other. In the example, 92.05% of visitors who have watched videos in the category “Space and Astronomy”, haven’t watched videos in other categories.