# How to project video viewcount based on historicals?

My goal is to create a formula that can give an indication of how a YouTube channel's video will perform in the first 30 days of its lifespan and eliminate viral video / "lightening in a bottle" outliers that may be on the channel. The goal is to use the resulting number to price a video from a specific YouTube channel.

As an example, a hypothetical YouTube channel uploads approx 10 videos a month. Variables:

1. Some videos get shared more and are more "viral"
2. Videos have a "fat head" and "long tail." Fat head refers to the largest chunk of viewership which in the case of established YouTube channels happens upfront, and the long tail refers to accumulated views over succeeding months.

These viewcounts belong to videos that the same channel uploaded in the last 30 days (from most recent in descending order):

  351,170
770,783
1,183,166
154,645
1,568,569
2,564,857
1,023,498
1,409,113
1,006,203
1,244,092


So my questions:

1. Is there a formula I could plug in to my spreadsheet given this data that could accurately come up with a conservative estimation of how the video will perform in the first 30 days?
2. If not, how can I create one?
3. Because some of these videos are still generating a "fat head" (like the most recently published video with 351,170 views) would it make sense to instead gather and average videos uploaded in the last 30-60 days instead? (fat head has time to impact viewcount and settle)
• Do you want to forecast the value for a specific video, or just be able to say 'the videos on this channel average X views in their 1st 30 days'? – gung Sep 14 '14 at 1:41
• @gung goal would be to say "Videos on this channel can expect to hit X by 30 day mark." I can figure out how to make the number conservative (math may be just as simple as slicing off 33% of the average we come up with) Forecasting value after that (money/pricing) becomes arithmetic and a lot more simple. – GPP Sep 14 '14 at 1:45