Growing TV Everywhere Adoption to 70%, Part 4: Enhancing Content Discovery

A hand reaches for a screen to discover content available via TV Everywhere.

Has anyone ever asked you “What’s on TV Everywhere tonight?” Probably not, because it’s a hard question to answer. There are simply not enough easy ways for pay-TV subscribers to explore and be alerted to what they can access via TV Everywhere.

As a result, further innovation in the area of content discovery would be welcome within and across TV Everywhere sites and apps. In fact, TV Everywhere can grow to reach 70% of pay-TV subscribers by the end of 2017 if pay-TV providers improve content discovery, increase consumer awareness and reduce sign-in friction for TV Everywhere viewers.

The current state of content discovery for TV Everywhere viewers

Most of the current methods for discovering TV Everywhere content leave room for improvement. Here’s a few of the most popular methods and their limitations.

  1. Browsing or searching TV Everywhere apps and sites
    Consumers can browse or search within the apps and sites provided by their MVPD or by TV programmers. Often, this method of content discovery doesn’t surface as much of the TVE catalog as the subscriber has access to. For example, a TV programmer’s app will only surface its own content. This isn’t optimal because it forces TV Everywhere viewers to go from app to app and site to site until they find something to watch.
  2. Using third-party services like Yahoo Video Guide, Yidio, or Molotov
    Consumers can create an account with services like Yahoo Video Guide or Yidio in order to get customized recommendations and email alerts about all their favorite TV programming across OTT and TV Everywhere services. Consumers in France will have a third option with Molotov, which begins service on July 11. These content discovery services could eventually provide the ideal experience for consumers. However, they’re currently falling short of the ideal because they’re asking consumers to install another app just for recommendations. The ideal consumer experience would be one app for both recommendations and playback.
  3. Using the interfaces of connected TV devices
    Makers of connected TV devices are also providing innovative content discovery experiences that put TV Everywhere content side-by-side with OTT content. For instance, Apple TV lets users search across multiple apps at the same time with Siri and will soon allow users to access any TV Everywhere app in the search results after providing pay-TV credentials just once. The only downside for consumers with these experiences is that they each only work on one device, a connected TV device. And connected TV devices only make up 23% of TV Everywhere authentications, which means these devices can’t provide a ubiquitous solution to content discovery.

The content discovery obstacles for TV Everywhere

Bottom line, every interface to TV Everywhere needs improvement. This includes all the “pull interfaces” where viewers go to search and browse for content. It also includes all the “push interfaces” where viewers passively receive recommendations.

Here’s some minimum requirements for pull interfaces:

  • Every site and app needs search and browse functionality.
  • Every site and app should personalize the browse functionality for logged-in viewers.
  • Viewers should be able to easily tell the difference between full-episodes and short-form content.
  • Viewers should be able to filter out all the results that they don’t have access to.
  • Viewers should easily be able to see metadata about each movie or program.

Here’s some minimum requirements for push interfaces:

  • Viewers should be able to sign up for personalized email recommendations.
  • Viewers should have access to other ways, besides email, to receive notifications of new content. For instance, the social media accounts of MVPDs, networks, programmers, shows, actors, and actresses could all be used to alert fans to shows they’re likely to be interested in.

One way to quickly enhance your content discovery capabilities is with Adobe Primetime Recommendations. This solution uses machine learning to intelligently surface data-driven, personalized video recommendations to your viewers, which they can play back instantly.

A bright future for content discovery

Competition and innovation in the area of content discovery will eventually correct for today’s limitations. Every player in the pay-TV industry will be a part of making the deep catalog of TV Everywhere content available to viewers. In addition, social networks will play a larger role in content discovery.

Moving seamlessly from awareness to content discovery to sign in

This information about content discovery completes my series on the three critical stages in the consumer’s TV Everywhere journey. Specifically, the ideal TV Everywhere journey is one where viewers:

  1. Know about TV Everywhere and the fact that it gives them access to premium content across hundreds of sites and apps.
  2. Discover content across these hundreds of sites and apps.
  3. Play the TV Everywhere content they’ve found without being slowed down by cumbersome sign in requirements.

The pay-TV industry has a lot to gain by optimizing these stages. They can increase the amount of time that viewers spend with their content, increase the loyalty that pay-TV subscribers feel toward the pay-TV brands that they engage with, and decrease churn.

Horia Galatanu

About Horia Galatanu

Horia Galatanu is Senior Product Manager for Adobe Primetime entitlement where he leads the strategic vision, product roadmap, priorities and key industry partnerships for Adobe’s TV Everywhere efforts. He has led the team from idea to eventual position as the industry’s leading solution for TV-E. He is a frequent speaker at industry conferences including OATC, CTAM, Streaming Media and TVOT and has spoken at TEDx about how easy it is to dismiss great ideas that don’t fit your viewpoint. Horia is a computer scientist by background and in the past, has led technical teams on online video. He has a bachelor’s and master's degree in computer science from the Polytechnic University of Bucharest.

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