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February 6, 2018

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How Big Data is Helping "Personalize" the PayTV Industry

In today’s catch-up race for pay TV providers to integrate new technology and forms of content, data becomes essential. Operators must understand viewing patterns in content consumption as well as the users’ interests and preferences towards content, menus, and genres in order to provide a more compelling and personalized user experience. This roughly translates to rapid processing of immersive user data provided by the CPE side, as well as predictive analytic solutions to segment subscribers based on their viewing pattern, which cue  recommendations and prioritize media delivery.

 

In an effort to compete, cable operators are increasily migrating their traditional service platforms to Big Data- based intelligent systems. Data compiled from this system is seen as a way to gain service competitiveness, to increase monetization and to create new revenue streams. Once only used in a web-based advertisement arena, this compilation of data is now being used by cable operators as a way to “personally” advertise to their consumer through the use of dynamic ad insertion, integrated management of content and management of promotional content and product packages based on how the viewer uses their subscription.

In December, it was announced that three large cable MSOs formed an “interconnect advertising platform” in the New York market. Deemed a “one-stop shop advertising solution”, advertisers can now use the data these three MSOs have compiled to reach the market’s 6.2 million households across the DMA rather than relying on vague program “ratings” of the past. As the article points out, the US Cable TV industry is highly matured and saturated and offers an “integrated targeted platform” which help advertisers reach the largest audience on a small budget.

In addition, the Big Data-based intelligent system compiling this data also allows for a scalable, flexible architecture for expandability and is easily serviceable by providing a backend business interface, thus decreasing operator costs.

‘Data’ is always tagged with ‘personalization’. Millennials who predominantly drive the viewing trends these days are easily switching their subscriptions. Therefore, pay TV providers must provide targeted services to specific users while keeping their costs to a minimum and an end-to-end big data based intelligent system is one way to do that.  

 

Posted by Jill OToole at 4:09 AM