AI: 4 ways it can help a pay-TV provider
Artificial intelligence means applying data science and machine learning algorithms to a large amount of data, in order to enable machines to perform intelligent tasks.
For a pay-TV provider, this means taking both internal data (about content consumption, quality of service, device usage, transactions and interactions with subscribers, and the content itself) and external data (household demographics, deep data on content and social network trends) and using it continuously to create smart actions that improve business metrics.
More than just analyzing subscriber behavior, it’s about improving key revenue and cost drivers in four main ways.
1)Driving subscriber value: personalized marketing
Algorithms can quantify each subscriber’s behavior, tastes, and trends, as well as the happiness generated by specific pieces of content or by complete pay-TV services. This allows the provider to create personalized experiences that raise user satisfaction and personalized marketing actions that improve the bottom line by increasing usage, preventing churn, driving upsells and encouraging the adoption of new services.
2) Driving content management
AI can help a pay-TV provider determine the content it acquires, and how it packages and markets that content. By modeling subscriber tastes and behavior, AI helps to quantify the value of every channel and every piece of VOD content, so a provider can maximize content efficiency in terms of happiness generated per content dollar invested.
Individual happiness counts: a provider can use AI to make sure that there is an offering that makes every user segment happy. A niche channel may bring limited value to the average subscriber but may be an essential element for specific users. Content also needs to be tailored to the delivery channel, as people consume different content on mobile and on their main TV screen.
For linear channels, AI can help a provider to optimize the cost of channel acquisition and delivery, including replay and start-over functions; for VOD, it can optimize the cost of content acquisition and possibly encoding.
3) Driving operations
AI can help to improve operations in resource-intensive areas such as call centers, to predict and reduce the cost of CDN and to manage the quality of video on OTT services. For instance, OTT video quality is never guaranteed, especially on mobile devices, since it relies on both open devices and the open internet. AI can automatically diagnose video quality and network problems (still the #1 churn factor on OTT) and help to create personalized retention campaigns for the people affected.
4) Driving addressable advertising
Pay-TV has a huge audience and captures a great deal of user attention. There is still a large pool of untapped value here, since when advertising becomes targeted, advertising revenues can be increased significantly.
Pay-TV providers hold the key to this increase, as they own the key data for profiling subscribers and delivering the right ad to the right user. AI can be used to support targeting by quantifying individual subscriber demographics, household composition and tastes. It can also be used to understand viewing behavior, to predict the available ad inventory for any ad targeting.
