Information – not just content – is king. While many industries have harnessed this new currency, the pay-TV industry, and cable operators in particular, have been comparatively slow to adapt to the new data- and AI-driven world. Few have been able to properly collect, implement and use data to gain valuable insights and improve their pay-TV service.
Those that have made the investment in data analytics tools and systems have often taken a short-sighted, siloed approach where different data sources do not talk to each other. Whether it’s from IT, marketing, or sales, each line of business within the organization is working in an information vacuum, preventing them from having the ability to make the business decisions needed to grow and deliver the services consumers want.
This is a major issue for pay-TV service providers in a world where OTT and social media platforms, such as Netflix and Facebook, have built their success on the ability to capture, analyze and act on data and AI to deliver a sticky experience.
There is significant opportunity — and a lot of work to do — to put the right solutions in place to ensure pay-TV operators can properly access and leverage the right information needed to ensure an unprecedented subscriber experience with their pay-TV services.
So how can pay-TV make the most of data and AI and use it to their advantage?
There has never been a more critical time for service providers to review their data and analytics strategies. Of course, pay-TV operators have legacy platforms to consider in the process – which OTT platforms do not have to contend with. However, when making the shift to embrace data analytics, they can do so while taking advantages of new technologies like AI, whether in the form of algorithms or machine learning.
In this context AI is a game-changer. It is not a replacement for the talent or resources in a service provider’s operations, but a way to help scale this talent and take those skills to another level by delivering a more compelling and engaging service to their subscribers.
Operators need to think of ways to leverage the value that data and AI can provide. To accomplish this, a transversal approach that spans every line of businesses across an organization is vital.
Three considerations must be addressed to ensure success:
First, a common language, a structural, harmonized way of collecting and using data should be implemented, while of course ensuring data quality.
Second, leveraging data and AI needs to be a top management directive to ensure the initiatives are followed and successful. It cannot be driven from just one department.
Lastly, start with identifying the business issue(s) to be resolved then look for the relevant data and algorithms– not the other way around. Service providers first need to identify which real, tangible business challenge they wish to address with data: What issue do we want to solve with data? Do we want to address churn? Can we implement predictions and recommendations to address it? What is the best way to encourage the use of the service? Is it a marketing action? Is it recommendation action? This is where AI comes into play and generates actions to ensure the service is optimized and properly used.
With a strong approach that takes all three of these factors into account, operators can implement a strategy that can leverage data and AI to drive subscriber value, content acquisition and management, operations and advertising and:
- Generate a coherent subscriber profile that quantifies behavior, tastes and trends. This enables the ability to predict the propensity to churn, helping service providers create personalized experiences that increase user satisfaction and develop marketing actions that convert more effectively, to improve acquisition, retention and service usage.
- Deliver content that increases subscriber happiness. Service providers can increase the usage of their services, quantify the value of every channel, program, catch-up content or VOD content by combining consumption and purchase behavior data, as well as learn how to optimize content packaging.
- Advance resource-intensive areas by improving operations across the content delivery chain to increase speed of diagnosis of network issues, optimize CDN costs and manage the quality of video displayed on OTT services.
- Increase programmatic TV advertising revenues by generating highly targeted and relevant micro-segments, better manage available ad inventory and increase advertising value.
While there is no “one-size-fits-all” solution, these considerations are key to ensuring that the investment in an effective data and AI strategy will deliver long-term business revenue and success.
With the right approach in place, data and AI can be a game changer for the pay-TV market which is well-positioned to leverage all that they have to offer.