Archives For youtube big data

We get a lot of questions about what metrics we use to calculate the vidIQ Score in Vision, our awesome YouTube Chrome extension for brands and creators. The short answer is – a lot! It’s Big Data science, really. The long answer is, everything here:

Watch Time
  • Average Watch Time
  • Views
Metadata
  • Titles
  • Tags
  • Description
Popularity of Creator
  • # of Subscribers
Virality
  • Facebook Likes
  • Facebook Comments
  • Facebook Shares
  • Tweets
  • Reddit
  • StumbleUpon
  • Google+
Recency
  • Age of Video
Engagement
  • YouTube Likes
  • YouTube Comments
  • Subscriptions Driven

Of course, all these metrics aren’t weighted equally – for the curious mind, here’s a live action reenactment of how vidIQ mad scientist/CTO Todd Troxell came up with the vidIQ Score formula:

How Do I Improve My vidIQ Score?

Since the purpose of the vidIQ Score is to judge the likelihood of your video surfacing in YouTube Search, Related Videos, and the Front Page, the best way to improve it is to focus on discoverability. That means Tags, Average Watch Time, Subscribers, Views, how old the video is, and social engagement metrics are mighty important! To improve these metrics, boost your discoverability on YouTube, and increase your Score check out this article by our CEO Rob Sandie on Five ways to organically grow your YouTube audience, sign up for vidIQ, and keep on creating!

For more information on vidIQ Vision check out the White Paper or download the extension here.