Annotation close rate is the percentage of viewers who choose to close a video annotation instead of clicking on it. A low close rate indicates high engagement.
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Used to show a simple Metric or to draw attention to one key number.
Databox is a business analytics software that allows you to track and visualize your most important metrics from any data source in one centralized platform.
To track Annotation Close Rate using Databox, follow these steps:
Annotation CTR is a metric in YouTube analytics that measures the percentage of viewers who interacted with annotations on your videos, indicating their engagement level.
The Average Percentage Viewed metric calculates the average amount of a video that viewers watch. It measures engagement and can help creators determine which parts of their video are the most interesting to viewers.
The Comments metric represents the number of comments left by viewers on a YouTube video. It is an important engagement metric that indicates how viewers are interacting with the content and can help creators understand how their audience is responding to their videos.
Dislikes are a metric on YouTube that represents the number of viewers who have given a thumb down to a particular video. This metric is used to measure the level of audience engagement and can influence the algorithm's recommendation of the video to other users.
Shares is a metric that measures how many times a YouTube video has been shared across different social media platforms, indicating its virality and potential reach beyond the YouTube platform.
The Subscribers metric on YouTube refers to the number of users who have chosen to follow a particular channel and receive updates when new content is posted. It is an important measure of a channel's popularity and engagement with its audience.
The Views metric on YouTube shows the number of times a video has been watched. It includes both unique and repeat views and is one of the most important indicators of a video's success.
Views by Traffic Source metric shows the number of views generated by each source such as YouTube search, suggested videos, external websites, etc. It helps to understand which traffic sources are driving more views to your videos.