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Why Data is the New Oil Driving TV

Inna Zagrebelny
Updated May 10 2020
Inna Zagrebelny
Updated May 10 2020

With today’s raging competition in the Pay TV and OTT industry, the concern levels are going up. On one hand, the ever-growing amount of available options leads users to subscribe to several services simultaneously, while on the other, contract-free packages and lack of loyalty contribute to increased churn rates. While Netflix continuously pride their low churn rates, maintaining viewers is indeed a big challenge. How do they do it? Through technology. Netflix is not only a content company, although they are investing heavily in it, but they are also a technology company that allocates significant resources into development and perfection of both their platform and their infrastructure. But not all the Pay TV or Cloud TV operators are Netflix.

Data as the means to boost loyalty and reduce churn

There are multiple measures that service operators can take to overcome the reduced customer loyalty and churn challenge: from improving content discovery and getting the right content in front of the right user, introducing interactive sports experiences, combining ad-based and subscription models for increased flexibility, all the way to adopting advanced technologies for easy delivery of new features.
When you look at all those measures, they have one thing in common- data. Therefore, to remain relevant and stay in this highly competitive game, service operators need to harness the power of data, and the sooner the better. Through deep understanding of the user-base characteristics coupled with analysis of content consumption and viewing habits, service providers can create more targeted and personalized offerings for their subscribers. This will allow them to keep their audience more engaged with the service and at the same time meet their business goals.

Audience segmentation is key for tailored experiences

To begin with, operators will have to identify the right audience groups, by implementing advanced segmentation models. It is essential for those models to be flexible enough- as viewing habits constantly evolve, the models need to be dynamically adjusted to reflect the most up-to-date user segments at any given time. Then, they must be able to define the most suitable offer to be displayed, whether it’s a single piece of content, a collection of titles, or an SVOD, TVOD, or a coupon offer. At the same time, TV service providers will have to identify the right time to present the offers and promotions for each segment, in order to create the most effective impact on the viewers. Finally, a proper communication channel will have to be utilized to ensure the viewers are aware of the promotions, personalized content, or special offers in the most efficient way.

 

This brings me to the conclusion that the transformation from the traditional broadcast to the dynamic Cloud TV service has become a necessity. As Cloud TV brings together the agility and speed of OTT alongside the robustness and scale of Pay TV, it enables to take the personalization a few steps forward. The addition of an intelligent data processing layer plays a significant role in TV services’ success in delivering tailored experiences, that is so essential to keep up with this market’s rapid evolution, and only with migration to Cloud TV such addition can become a reality.

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