Christopher Rae, SVP of Global Operations, Verimatrix, gave his insights on video services prior to the 2019 Future of Video: OTT, Pay TV, and Digital Media.

Christopher participated on the research workshop session Piracy: A Billion-Dollar Challenge with Steve Epstein, Head of Innovation and Distinguished Engineer, Synamedia.

What is the greatest disruption to the entertainment industry?

There’s a downward spiral with all of the new direct-to-consumer SVOD services coming to market which is that there’s too much content, too much choice, and subscribers are nearing a breaking point of having to have a Netflix, Amazon Video, Hulu, Disney+, Apple TV+, ESPN+, HBO Now, Showtime, Stars, CBS All-Access, YouTube TV, etc. accounts. Subscribers will start to churn on OTT services (or at least move to smaller packages, such as cancelling their Hulu Live package at $54.99/mo to go with Hulu Basic at $5.99/mo), and this will drive more piracy because the demand is only going to get greater for their great quality content, but willingness of consumers to pay will drop with so many subscriptions. The OTT churn isn’t going definitively push users back to cable and satellite bundles because much of the desired exclusive content is not available there and a primary driver of their leaving earlier was total cost, which will further drive even more content piracy and operator service theft, but we will see them starting to create their own exclusive content as well. This churn and reduction of revenue will threaten the economic viability of making so much content, and there will be consolidation of the marketplace that forces increased M&A activity, and/or walled gardens to fall, and content will need to be syndicated between services. Unless, of course, more of the piracy activity can be intelligently converted to paying customers. 

How will advanced technology most likely to affect video services?

Artificial intelligence and machine learning will increasingly affect all aspects of video services from production to distribution to revenue generation to anti-piracy. It will continue to emerge in any place where there’s an opportunity to manage efficient real-time operations faster and at scale; where identifying hidden anomalies, correlations, patterns and trends in large data sets; and where systems can should be learning, adapting, and continuously improving themselves and with more data points over time, to help business leaders make more informed decisions, such as in the continual anti-piracy battle. 

What is the next stage of evolution of OTT video services?

To combat subscriber churn and to disincentivize further piracy, service operators will start to experiment away from all-you-can-eat OTT pricing, and start to come up with different personalized pricing models. This will then create a golden opportunity for someone to create a simple, unified storefront experience to aggregate content and provide the consumer with a personalized pricing model (example: I’m willing to pay a premium to binge all the new episodes of “Succession” from HBO, “Black Mirror” from Netflix, “Billions” from Showtime, and “Mr. Robot” from USA Networks, but am willing to wait each week for “Its Always Sunny In Philadelphia” from FX.”) Other models may include metered plans, longer term contracts for bigger discounts, free or discounted with less obtrusive omnichannel advertising, etc. 

In the next 2 years, what changes in the user experience will occur? 

• Authentication: Getting rid of usernames and passwords as authentication solutions (and sources of credential theft) in favor of contextual solutions that recognize your identity from proximity of you mobile device, facial recognition, etc. and which are available as you travel (e.g. when you check into a hotel, the TV automatically loads with your Netflix, Amazon, Hulu, Disney+, HBO, etc. accounts seamlessly) as well as being able to identify who in the room is watching to cater the advertising and recommendations to them. 
• Pricing Models: Pricing models that allow you to pay a premium for binging an entire season at once, or paying a standard price to get the content on a weekly basis; metered pricing based on how much is consumed, and longer-term commitment discounts. The flat fee model for all-you-can eat will still exist for those trying to win market share who have other sources of revenue (Disney, Amazon, Apple, etc.) and can wait it out to starve their competition who is relying solely on SVOD subscription revenue which will become at-risk once there’s too much service fragmentation and users begin to churn. 
• Content Customization: The technologies will emerge to personalize content to the viewer. This might even mean you and I see different endings to a movie because I prefer dark tragic endings and you prefer happy, feel-good endings. This may also become a differentiation factor against piracy as a service with your preferences, history and inputs is going to provide you with a reason to subscribe to get a customized version of content you can’t get (or get as easily) through pirated services that all share the same version of a movie or show. (Think “Bandersnatch” but with many more potential paths, and an automatic option to let the service pick your preferred narrative storyline based on your viewing preferences and history.)
• Content Recommendations: Smartphones and other devices will use daily contextual clues to make predictive content recommendations and make choices for you (e.g. “Your commute on the 405 is taking much longer than normal due to the rain after you spent all day in back-to-back meetings, and you didn’t have time for lunch so your blood sugar must be low and you are probably cranky. Here’s a list of recommended action movies organized cathartically from largest number of cars getting blown up for you to choose from while I call Uber Eats to order your favorite comfort food to be delivered a few minutes after you get home. If you don’t make a choice in 10 seconds, I’ll choose the Michael Bay movie for you.”)
• Integrated IoT Advertising: Your smart refrigerator will detect it is low on milk, so the next few ads on TV are for different milk options with a “Buy Now” prompt between choices, and once the choice is made, your refrigerator will subscribe to have new milk delivered based on your projected consumption rate and the expiration date). Inversely, your TV will note that you’ve been watching a ton of Asian cooking shows on Netflix and use image recognition and meta data to make recommendations on things to add to your shopping cart based on the episode (“Would you like to buy these ingredients to learn to make miso black cod? Please click ‘Yes’ or ‘No’”) or prompt you to order that from your nearest/favorite pan-Asian restaurant for delivery in 30-45 minutes. TV services may opt for not showing ads during the shows in exchange that you’re willing to see more omnichannel ads on your mobile device, email or social media streams, or with proofs-of-purchase from their advertisers. 
• Shared Experiences: There will be more technologies and services that allow people to share experiences at the same time in different locations similar to Twitch. It will expand from e-sports gaming and viewing parties for a particular episode, to synchronized binge watching of shows with your friends. Content owners will create business models and events where people can attend movie premieres, sporting events, etc. together online, and it will create a new challenge for anti-piracy efforts that can be solved at scale with AI/ML. 
• Spoiler Avoidance: There will be deeper integration of social media and content services to identify whether you’ve watched the latest episode of a show or not to help filter spoilers including the perpetuation of memes, GIFs and video clips via image recognition for those who haven’t yet caught up.

What is the future of pay TV in the next 12-18 months? 

On a long-enough timeline, pay-TV will continue to become more integrated, more automatic, more personalized, and more on-demand, with the exception of breaking news and sports. A potential consequence of this, much like social media, is that it will create silos and bubbles where people are not exposed to the same news sources and information (or even same version of a show or movie) at the same time, which can reinforce confirmation bias. Some services and technologies like Twitch will bring groups back together for shared experiences, but there will also be services that attempt to better mix things up and introduce people to things outside their typical comfort zones using deeper insights from larger data sets over time to expose the content to larger audiences (“I know you don’t like scary horror movies, but here’s a vampire movie with the type of comedy you’ve liked before, featuring this actress you follow on Instagram, and with a soundtrack that closely mirrors your recent Spotify listening habits.”). Simultaneously, other services will double-down to create content that is uniquely personalized for the viewer in a way that creates stickiness to the service, and makes it harder to steal and share.