New YouTube Analytics interface and features: Check out our AFL Grand Final data viz video stats

YouTube just announced the next generation of their video analytics feature which uses the same data as the old Insights tool. To be honest, not much has changed apart from an interface design upgrade but it's nice to see that this has become a focus again and we can only hope this will get included into Google Analytics at some stage.

Check out the video stats from our recent AFL Grand Final Twitter data visualisation to get an overview of what's on offer in the new youtube.com/analytics tool. As you can see we're certainly not a video production house and don't get millions of views but the AFL video was a nice spike for us - never had more than a hundred views before!

The data shows us that the majority of views originated in Australia and came mostly from males between 25-54 (surprise surprise). Interesting to see is that mobile was much bigger than anticipated with almost 25% of views. I really love the video retention reports though, they're are awesome to optimise your actual video content (and I hope more companies will start using this to improve their TV ads). In the case of our AFL video you can see that we have a fairly steady drop-off of total viewers during the video but compared to the average (which is great benchmarking data) are actually doing pretty well in getting viewers to watch the video to the very end. 

Read the YouTube analytics guide for a more detailed explanation of the various reports.

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Interesting testing approach by YouTube allowing website visitors to opt into and explaining test

I just came across this interesting new testing approach on the YouTube home page that allows website visitors to opt into a test and also explains what's being tested instead of just randomly allocating people into test groups using the standard a/b/n approach. 

Giving choice to people is usually a good thing but in a testing situation that's kind of new and I'm not sure how I feel about this, what are your thoughts? Using an opt-in approach and explaining the test should generate more buy-in and maybe even unprompted feedback but I wonder what the non-random allocation of test subjects does to the significance of the test results.

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YouTube channel with easy to understand videos on statistical concepts such as regression analysis

For those of you who would like to get into the heavy stats side of data mining (or have accepted the fat that they probably have to), I just came across a great YouTube video channel thanks to Shailendra Kumar's blog, the current data mining lead at Woolworths (his blog is a great reas as well but a little more involved).

The StatisticsFun YouTube channel contains some really great videos with step by step explanations of statistical concepts including the below on regression analysis which is basically the mechanism behind the prediction of customer behaviour based on past transactions or the holy grail of data mining. How about watching a few stats videos of the Christmas break?

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New TED video from David McCandless on the power and beauty of effective data visualisation

This is a must watch video for all data fans, it includes a few cool data visualisation examples. David also talks about data being the new oil and tries to coin the new phrase of "data being the new soil" (i.e. insights and innovation spring from it), great idea I think but it comes across as a bit wanky. Anyway, awesome examples and great video!

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YouTube Insights for Audience: Discover what videos different audiences and demographics like to watch

Amazing source of information to get a deeper understanding of what triggers your audience interest. Below is a sample output showing me videos that 25-34 year old males in Australia like to watch including search terms used and how well they index by category. Nice!

Try the audience insights tool here
http://video-analytics.google.com/yap/iba

Or check out the other beta options
http://www.youtube.com/testtube

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