This blurring and viral nature of distribution chains means that measuring online video performance can be just as important to the success of a campaign as video ad performance. But whereas measuring video ad engagement is driven by the measurement needs of advertisers, online video playback is often measured by performance parameters like latency, the maximum number of simultaneous streams served, or by economic considerations like the cost per stream. Over time, as the boundaries soften, owners of online video will probably require the same sort of measurements as advertisers do now. This suggests that one way of looking at part of the future of online video is to look at video ads.
Video ads are different than online video content in many ways. A video site like YouTube has two ways of connecting viewers to video clips: Viewers either type in specific search strings, or get search strings sent to them via other channels such as email or television ('Susan Boyle' for example). Viewers can also get recommendations of popular YouTube clips, which lead to other related clips and even more recommendations. In contrast, video ads are carefully targeted at likely visitors to a Web site through a marketing message or an offer that leads the consumer to another site sponsored by the brand. This leads to two correspondingly different measurement approaches -- one aimed at video consumption optimization focused on keeping viewers on the site, and the other aimed at ad placement effectiveness focused on persuading viewers to go to another site.
Suppose that a serendipitous accident flips us into a parallel universe where the two types of content are swapped. Suddenly, YouTube becomes a very efficient way of finding video ads on any topic, and once the viewer has watched one, it suggests others that the viewer might enjoy, increasingly targeting its content (ads) according to the information that the viewer's selections provide. On another Web page, the familiar ad unit locations have transformed into charts of popular TV shows that lead to official sites devoted to that specific show, and clicking on any of these charts rapidly refines the targeting of the chart contents. So if you click on NCIS in the first chart, the next chart you see has crime and military shows, and if you click on "CSI: New York," then the next chart has related crime shows.
Back in the real world, it can be difficult to search for a specific advertisement, and the only way to find out about a TV show is to go to a listings site or the official show Web site. The status quo suddenly appears to be limiting when compared to the parallel universe -- could measurement benefit from the same crossover universe? When you consider measurement from this bird's-eye viewpoint, then it seems that the pushing of ads to viewers, and the pulling of content by viewers could both use an engagement-based measurement methodology.
One such powerful measurement technology comes from TubeMogul, which is commonly known as a distribution platform for video content. Its InPlay video analytics integrate with any Flash-based video player, and provide a variety of metrics on where, when, and how often the videos are viewed. It's important to note that this is not specific to video ads -- it can be used for any type of online video content.
As the lines continue to blur between information, entertainment and advertising content, it looks like the future of online video may also include the sort of detailed measurements that we currently apply only to video advertising. As the boundaries between the two decrease, the industry as a whole will benefit.