Taking media analytics over the top isn’t as easy as it should be
Being a data scientist or business analyst in media and entertainment is never an easy job. These individuals have no chance to kick back and say “mission accomplished.” The work is never done. With each passing quarter, a new data source emerges, a new model to operationalize is developed and a new way for getting closer to a viewer’s specific interests and driving enhanced, more repeatable streams of revenue comes to light.
Over-the-top (OTT) content is a perfect example of the rising challenges that studios, networks and media face. According to Wikipedia, OTT content refers to “delivery of audio, video and other media over the Internet without the involvement of a multiple-system operator in the control or distribution of the content.” OTT content is quickly becoming common and is an increasingly important source of large-scale streaming data.
Quick note: Some people think the term OTT should be retired before it catches on. Do you agree or disagree? Weigh in with your opinion in the comments.
Personally, I can tell you that I regularly consume OTT content through Hulu and Netflix at home, at the airport, at the gym and beyond on my laptop and smartphone. If you stop and think about it, I’m guessing you do the same thing. Mobile is a focal point both in and out of the family living room, either for a single or multiscreen experience. And with the rise of Smart TVs, Internet-connected gaming platforms, tablets and other connected devices—not to mention all the cord cutters—the days of linear, set-top box (STB) and DVR content consumption being the standard are quickly waning.
Because so many studios, networks and media companies have advanced analytics platforms in place that can handle large volumes, velocities and varieties of data, why is OTT content creating such a challenge? Turns out, two primary issues are at play here.
Issue 1: Getting to the hearts and minds of OTT content viewers isn’t as easy as it used to be
Access to or distribution of the analytics is the crux of this issue. For example, Netflix and several other OTT content sites do not provide any viewing statistics through analytics back to the client. Imagine laboring for months to create a painting. You finally get a museum to show it, but the museum won’t tell you how many tickets it sells, who visits the museum or the number of people who entered the wing in which your masterpiece is hung. And the number of people who actually stopped to look at your painting isn’t provided either.
While this lack of information may be a happy problem—meaning you’re happy to have a place to show the content even without the viewer information—it doesn’t change the fact that you can’t make an accurate business decision. You cannot make decisions for marketing, creative and so on based on sheer guesswork and social mentions. Analysis of social data can help add some pieces to the puzzle, but until OTT content providers iron out this data distribution issue, assembling a complete picture of any real-time content consumer will be difficult for anyone to accomplish.
Issue 2: Just when you thought you knew all the data sources, even more pop up
To add more complexity, just one OTT content source isn’t the only one you need to consider. A growing number of OTT content sources are emerging, and each one is producing its own unique data set. Only some sources are willing to share their data sets, but currently many others are not willing to share them. As the data distribution deals get worked out, OTT content data will inevitably become more voluminous—far more voluminous—than viewing metrics through linear media. Therefore, traditional metrics sources, such as Nielsen, become less weighted as a primary or singular source of viewer and customer data. They will always have a place in the process, much like focus groups and surveys still do, but they won’t always be able to get the real-time, in-the-moment story that media executives so desperately crave.
OTT content sources will be more readily available once we pass the discovery stage that we currently find ourselves working through in this media-centric space race. For this reason, I frequently talk to customers and conference attendees about investing ahead of scale, so the analytics platform is ready for the OTT content data of tomorrow and not just the linear data of today.
Accurate viewer profiling is the moonshot that media executives have been working on since the dawn of on-demand content. With each passing click, view and recommendation, broadcasters and networks need access to all viewing data for behavior-based audience insight and fan analytics, so they can make more informed decisions. And these decisions are about which programming choices they need to make and how to market to their audiences for effective, repeatable and predictable up-sell and cross-sell opportunities.
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