Pay-TV providers: finding a way forward in a shifting context
Let’s look at how pay-TV providers can address recent changes in their industry and learn from their OTT rivals, making better use of data and AI to drive their businesses.
Introduction
The pay-TV industry is suffering from cord-cutting and a decrease in ARPU, driven in particular by rapid changes in how people consume content. The industry is simultaneously being challenged by pure OTT players that surf on new user behavior and fully connected networks, leveraging their data using AI to drive every part of their business and obtain very high user engagement.
The early impact of this change in behavior went unnoticed by some pay-TV providers, who were looking at revenues and churn rather than engagement. Content consumption started first to decline, as behavior evolved. Later, as consumers discovered that they did not need traditional services as much — if at all — ARPU started falling and churn rising. Pay-TV providers were essentially looking at the wrong metrics.
But compared with the pure OTT players, the pay-TV providers have some major assets. They have a huge footprint and access to the widest available range of content. There is an opportunity for them to leverage this content using services that are available on-demand and everywhere — such as Replay TV, start-over TV, and NPVR — to provide their users with the content they love, wherever and whenever they want, on any device.
A look back at how pay-TV has developed in recent years
Complex infrastructure
Pay-TV providers have historically used a silo-based infrastructure, built for broadcasting pay-TV. Specialized technology vendors needed to support one-way networks and created powerful, complex technologies both in the headend infrastructure and within the set-top box (e.g. in order to prevent piracy). The complexity increased further as more advanced technologies arrived, such as PVR (personal video recorder) services.
This approach generated vast revenues, but it is now cumbersome and fails to respond to the new generation of online users who want to pick and choose the content they watch.
Mobile video and streaming: changing consumer behavior
Pay-TV businesses are changing the way they compete in response to changing users’ expectations.
With the explosion of internet video, consumer behavior started to change completely; as did their expectations of what pay-TV should be. Consumers have become used to immediate and frictionless experiences, optimized for consumption on their laptops, tablets, and phones.
The penetration of pure OTT players, such as Sling TV, Hulu and Netflix, is based on providing a great user experience and they have greatly contributed to raising users’ expectations.
They expect instantaneous, easy access to content, from a service that looks like it has been built just for them. They are used to personalized messages and content recommendations that are genuinely interesting to them. Personalization is no longer optional, it is essential.
Competition shifting away from price and towards user engagement
Pay-TV providers used to compete mostly against each other, typically satellite vs. cable vs. telcos.
Except for some premium sports content, the content available to all players was similar, and the competition was mostly around price and triple- or quadruple-play bundling. The details of the user experience and the success of individual pieces of content or channels generally attracted little attention.
New user behavior has shifted competition in the market away from simply annual pay-TV package price and towards the overall user experience. Players now compete on content catalog and overall user experience, which is driven by ease of use, content catalog, ease of discovery, personalization, and engagement.
User engagement, also known as service usage, is the new gold that will separate the winners from the losers, generating better acquisition, activation, retention, and upsells.
OTT providers: playing a different game
Low adoption barriers
Streaming services can be adopted immediately, on existing personal devices without needing a new set-top-box, cables or an annual contract.
This means that these services can offer trial periods and monthly subscriptions, further lowering the entry barrier for subscribers. They can easily be tested in addition to existing services. And they are designed to be simpler, easier to explore and cheaper than the existing pay-TV services with which they compete.
As content producers such as Disney move to B2C OTT offerings, consumers will increasingly pick-and-choose from various services — for instance, a basic paid package or free-to-air offering for live content, Netflix for its original series, and an HBO OTT subscription to watch Game of Thrones and other HBO hits.
Data-driven by nature
Because they don’t delve into the complexities of one-way communication, their systems are much more agile — everything is managed by servers — and they naturally provide a wealth of user data that is used to improve every aspect of the platform. A dialogue takes place between the platform and individual users about content consumption and discovery. This is used to improve the overall user experience, maximizing user engagement, which leads to enhanced (and cheaper) acquisition, account activation, retention, and revenues.
Netflix-like players came with a lean “try-measure-iterate” methodology. They knew that they had to create a great user experience to maximize their own business KPIs. And it worked. They are fully data-driven, using data and data science to manage nearly all aspects of their business.
Focus on user engagement and personalization
At Netflix, improving user engagement is strongly correlated to improving retention. In other words, the more specific users consume, as measured by the number of video hours they watch, the less likely they are to churn. When looking for content, typical Netflix users lose interest after 60 to 90 seconds. If users don’t quickly find something they want to watch, the risk of seeing them churning away increases substantially.
As a result, user engagement is the main metric that needs to be optimized, and personalization is a key driver of engagement. Netflix provides users with many different personalized ways to discover their content, powered by many different algorithms. And it works very well: Netflix estimates that personalization and recommendations together save more than $1 billion per year.
Netflix also creates several thumbnails for every movie and then presents them automatically to users, to measure which thumbnail generates the most views for each type of user. The next tranche of users is then shown the thumbnail most likely to perform just for them.
More happiness per dollar spent on content
Netflix now understands the tastes and behavior of its subscribers. It uses this data to decide what content to acquire or produce, and at what price. Data enables it to predict how much interest a future piece of content will generate in its subscriber base, based on parameters such as the actors, director, and success of similar content. Netflix seeks the most efficient content, i.e., that generates most happiness per dollar spent on licensing or production.
