How To Rank In YouTube – YouTube Ranking Experiment #1 (Artificial Traffic)


In this case study series, I will be running a number of experiments in order to figure out exactly how to increase the rankings of target keywords within YouTube's SERPS (search engine results page). IMPORTANT NOTE: This series will not be focused on how to rank YouTube videos in Google SERPs. I will add a link here later for those experiments.

This specific experiment will focus on using artificial traffic from a free to use tool called Pandabot (learn more here & here). Explained briefly, your Pandabot tool browses other people's content for which you accrue credits. You can then exchange those credits for views on your own content. Essentially, It's an advanced view exchange system with lots of features.

If you want to test this tool for yourself, you can get the Pandabot tool here.

Test #1

Upload date: 3rd of June 2017

Duration (HH:MM:SS): 00:02:21

Panda Campaign start date: 22-Jun-17

Views sent daily: 5

Traffic Sources: Mixed locations. Arrive at video via specific keyword searches.

None

After a month of running a steady stream of 5 views per day, there does appear to be a small SERP increase overtime. This could have been a natural increase from genuine traffic, but in any case, 5 views per day will unlikely be enough to push rankings to page 1 quickly.

Test #2

Upload date: 30th May 2017

Duration (HH:MM:SS): 00:02:14

Panda Campaign start date: 19-Jun-17

Views sent daily: 10

Traffic Sources: Mixed locations. Arrive at video via specific keyword searches.

Huge leap in progress very quickly. After closer inspection, I'm not convinced Pandabot was completely responsible for the leap. See Results + Conclusion.

How To Rank In YouTube - YouTube Ranking Experiment 2.3

The experiment will continue with 10 views per day. However, it doesn't appear all the views are being registered on YouTube. As you can see from the stats, less than half of those views are being registered. The experiment didn't start until the 19th (highest peak in views), so it looks like natural views (real youtube users) from the 15th to 18th are responsible for the initial spike in rankings (see graph in results). Although the rankings climbed further after the experiment started they have reached a plateau.

Update:

Having looked into this further by checking the YouTube video analytics, it appears only one quarter of the views sent by Pandabot were registered on YouTube.

Test #3

Test3

Upload date: 1st Jun 2017

Duration (HH:MM:SS): 00:02:04

Panda Campaign start date: 22-Jun-17

Views sent daily: 10

Traffic Sources: Mixed locations. Arrive at video via specific keyword searches.

None

Gradual increase in rankings as can be seen since the campaign started on the 9th.

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