Long standing content distribution arrangements are being dismantled. Media companies are gearing up for battle for eyeballs and engagement by taking their content directly to consumers bypassing Multi Video Programming Distributors (MVPDs). Almost every media company has already launched their own Direct to Consumer product, or they have plans to do so in the near future. Entrenched streaming services have a lot to lose, but have an early advantage in terms of technology and embedded subscriber base. The battle has just begun and is in the early innings. However one thing is clear, media companies want the middlemen out and go direct to the consumer with their Over The Top (OTT) content. To garner consumer interest, they are sprinkling exclusive content, lower cost, and a frictionless user experience.
No doubt delivering compelling content consistently could tip the scales. However, if the same content is available via the MVPDs, will the consumer go through the hassle of buying content from many OTT offers? Would there be OTT fatigue? Big Media is betting against it. Execution and speed to market is key to success.
For DTC initiatives, media companies must now get smart on standing up and operating massive content delivery infrastructure. Predicting consumer preferences, fickle as it is, can be challenging while trying to keep the subscriber base engaged. In addition, they will also have to establish a direct billing relationship with the consumer and ensure they do not churn out.
Infrastructure decisions about cloud vs on-prem has to be made. Media companies have to engineer, deploy and operate infrastructure for Transcoding, Packaging, Origin, CDN, DRM, Video App for many flavors of devices and also be able to process user analytics and intelligence--all of which requires acquiring new sets of skills and capabilities. Having built and launched OTT infrastructures that millions of users use daily for MVPDs, BusinessOne brings unique capabilities that can help accelerate and scale DTC objectives.
Understanding the user experience is critical for evolving the video experience for consumers. Analyzing how long users browse or search for content, what programs and shows they watch, how long they watch, can all drive personalization and recommendations which require capture, analysis and engineering of screen/menu navigation data, click stream data, device logs and other server side data, at scale--by no means a trivial task.
Each customer is different and being able to mass customize and personalize recommendations requires not only the ability to squeeze insights out of data but also ML capabilities. Behaviors like binge watching, skipping intros, auto tuning to next episodes, thumbnail animations, and recommendations, are all capabilities enabled by ML. We can help you dominate the battle for eyeballs and engagement.
ML for content engagement is not only about providing facts and figures about how long the users are watching, what they are watching, where they are watching, ad engagement, what device etc, but also about predicting customer preferences, which then guides the decision about what content to place on the platform. This provides an additional tool for Media companies, as well as MPDUs, that would help make the right decisions about what content to offer and perhaps provide some bargaining leverage.
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