Netflix, the global poster child for streamed TV and the use of Big Data to inform the programs they develop, has shown steady customer growth for several years now. Recently, the company revealed that it would be shutting down the user reviews which have been so prominent in their media catalogue interface for so long.
In the background, media and telco are merging. AT&T, the telco which undertook the biggest deal in history recently, acquired Time and wants HBO to become like Netflix. Telia, a Finnish telecommunications company bought Bonnier Broadcasting in late July 2018.
The video content landscape has changed a great deal in the last decade. Everyone in the entertainment game wants to move beyond broadcast TV and to use data to develop content their users will love and which will give their customer base more variety. This means they can look to data to charge higher subscription rates per user, experiment with tiered subscriptions, decide to localize global content, globalize local content and more.
These changes raise two key questions. First, are we heading for a world in which AI and ML based algorithms drive what we watch on TV? And second, are the days of human recommendation being quietly replaced by machine recommendations over which the user has no control?
To get an insider’s view on the answer to those questions, I sat down with Matt Jones of OVO Mobile, one of Australia’s fastest growing telecommunications companies. OVO offer their customers a unique point of difference – streaming video sports content, included in a phone plan. OVO has bought the rights to a number of niche sports in Australia which weren’t previously available and now offer free OTA (Over the Air) digital content for fans of ‘unusual’ sports like Drag Racing or Gymnastics.
OTA content is anything delivered to a user’s phone over a wireless network. In OVO’s case, the data used to transport the video content they provide to their users is free. That means customers don’t have to worry about paying more for mobile data so they can watch it – a key concern for users.
- What’s changed our media consumption habits: the ubiquitous mobile internet, the always on and connected younger generation, better mobile hardware, improved network performance and capabilities, need for control over content choices.
- Digitization allows new features –some of which that people have proven to love – binge watching, screening out advert breaks and time shifting.
- The key to understanding the value of ML and AI is not in understanding the statistical or technical models that are used to enable it, it’s the way AI is used to improve the customer experience your digital customers are having with you.
- The use of AI in digital/app experience has changed in a way to personalize what users can see which old media could not offer. Content producers use the information they have on us, about the programs we watch, when we watch them and for how long we watch to
- Contribution of AI / ML towards the delivery of online media is endless in terms of personalisation, context awareness, notification management etc.
Social acceptance of media delivered to users on mobile phones is what’s driving change
A number of overlapping factors are driving changes in how we engage with content. Social acceptance of the internet and mobile access to it as a core part of life is one key enabler. From a technology perspective, things have changed too. Smartphones now have bigger, higher resolution screens than ever before – and they’re with us all the time. Jones believes this change is part of a cultural evolution in how we relate to technology. He says,
“There has also been a generational shift which has taken place. Younger people are used to the small screen being the primary device. They’re all about control, seeking out their interests and consuming these, as opposed to previous generations which was used to mass content distribution from traditional channels like TV.”
Other factors include network performance and capability which has improved dramatically in recent years. Data speeds have grown exponentially from 3G networks – launched less than 15 years ago, which could support stuttered low resolution video to 4G and 4.5G enabled networks. These can now support live streaming of High Definition TV. Mobile data allowances in plans and offers from some phone companies to provide some content ‘data free’ (as OVO does with theirs) have also driven uptake.
Finally, people want convenience and digital offers that in a way people have never experienced before. Digitization allows new features –some of which that people have proven to love – binge watching, screening out advert breaks and time shifting.
What part can AI / machine learning play in the delivery of media online?
The key to understanding the value of ML and AI is not in understanding the statistical or technical models that are used to enable it, it’s the way AI is used to improve the customer experience your digital customers are having with you. When you find a new band in Spotify, when YouTube recommends a funny video you’ll like, when Amazon show you other products that you might like to consider alongside the one you just put in to your basket, that’s AI working to improve your experience.
“Over The Top content is exploding. Content owners are going direct to consumer and providing fantastic experiences for their users. What’s changing is the use of AI in digital / app experiences to personalize what users see in ways old media never could.” Says Matt.
Matt’s video content recommendation app, for example, ‘learns’ not just what you like to watch but also the times you are most likely to watch it. It then prompts users with a short video to entice them to watch. And the analytics available show just how effective it is. Matt’s app can be up to 5 times more successful at encouraging customers to watch his content, than those who don’t use it.
“The list of ways that AI / ML contributes to the delivery of media online is endless. Personalisation, context awareness, notification management …. Endless”
By offering users recommendations on content they’ll love, producers can now engage more customers for longer. Content producers use the information they have on us, about the programs we watch, when we watch them and for how long we watch to:
- Personalise at volume: Apps used to deliver content can personalise what’s shown first to users, based on a number of variables known about them, including the sort of context awareness that can be relatively easy to find on mobile devices. Ultimately, every AI customer experience improvement (including the examples that follow) are all designed to automate the process of providing something special to each individual that they uniquely want. Automation means that can be done at scale, with every customer treated uniquely.
- Notification management: AI that tracks the success of notifications and acknowledges, critically, when they are not helpful to the user, can be employed to alert users only about things they want to know. These AI solutions provide updates to users based on their preferences and avoid the provision of irrelevant information.
- Content discovery & Re- engagement: AI and ML can be used in the provision of recommendations as to what users could watch, which expose customers to content they would not otherwise find, but which they are likely to value.
- Better / more relevant advertising: Advertising which targets a legitimately held, real, customer need is actually useful to viewers. Better analytics for AI can assist in targeting micro segments with ads which contain information customers will value. Lattice, is a Business Insights tool provider. Their ‘Lattice Engine’ product combined information held in multiple cloud based locations and uses AI to automatically assign customers to a segment which suits them. Those data are then provided to a customer’s eCommerce site and other channel interactions, and used to offer content which will help them convert better.
- Developing better segments: Raw data on real customers can be gathered from digital content systems to inform Above The Line marketing in the real, non digital world. Big data analytics can now be used with accurate segmentation for local area marketing and to tie together digital and retail customer experiences. McKinsey suggest that 36% of companies are actively pursuing strategies, driven from their Big Data reserves. They advise their clients that Big Data can be used to better understand and grow Customer Lifetime Values.
- In the future – Deep linking for calls-to-action: Some digital content is provided in a form such that viewers can find out more information about an item on screen. Providing a way to deep link from a video screen in to a shopping cart prepopulated with something just seen on screen is an exciting possibility for the future. Cutting steps out of the buying process to make it easier for eCommerce users to transact from within content apps to buying a product they’ve seen on the screen is likely to become a big business. Deep linking raises the value of the content shown to the degree it raise the sales of the products included.
Bringing it all together
Jones believes those that invest big in AI and machine learning, and of them, those who find a way to draw out insights and act upon them, will be the ultimate victors.
“The big winners are going to be the people who connect a fan with content they love and use AI and ML to deliver the best possible experience. It’s about using all the information you have about your users and acting on them.” Said Jones.
That commercial incentive is already driving behavior. AI and ML drive already provide personalized content recommendations. Progressive content companies, including Matt’s, are already working on building AI in to every facet of every Digital experience you have.
As to whether AI is entirely replacing social media influence, I don’t think that’s the case. The research says people are still 4 times more likely to watch a video if it is recommended to them by a friend. Reviews have always been important to presales on the internet and that applies to TV shows, too. People want to know what real users felt when they used a product. If they can’t get reviews from Netflix, they will simply open a new tab and google for reviews in that while they are thinking of how to find something to watch on Netflix.
About Matt Jones,
Matt is an industry disruptor, launching the first of its kind Media and Telco brand OVO Mobile in 2015, Matt is the driving force behind convergence of new media & telco – by bringing together Telecommunications with Media Rights and digital broadcast for mass distribution.
OVO is a new type of Telco, delivering content that fans are passionate about, streamed live on their mobile or tablet UNLIMITED & data free. OVO has secured exclusive 3 year+ digital broadcast and distribution rights for a range of content owners including Supercars, World Superbikes, 400 Thunder Drag Series, Audi Australia Racing & Gymnastics Australia – with a combined Australian audience estimated at over 7 Million.
OVO is a multi-award winner, including winning the Money Magazine Best of the Best Award 2017 for high usage, as well as featuring on A Current Affair, Sunrise, The Today Show, Channel 7 News, Channel 9 News and multiple radio shows for their world-first kids’ mobile phone plan with built-in cyber security protection.
As OVO CEO, Matt was nominated for Start-Up Executive of the Year at the CEO Magazine Awards 2017 and was awarded runner-up. The Award recognises the achievements of leaders and professionals, and the contributions they have made to their companies across industry-specific categories.
Matt holds a Bachelor of Arts (BA) from the University of Tasmania and regularly speaks at Telco, Sports Marketing and Media forums and events. Matt has held executive leadership roles at leading Telecommunications brands including Telstra (Head of Strategy – Operations), Optus, Vodafone, AAPT, Telecom New Zealand as well as global Management Consulting firms including BearingPoint.
Matt lives on the northern beaches of Sydney with his wife Mel and daughters Charlotte and Lucy.