Who should tell you ‘what’s on TV tonight’?

Who should tell you ‘what’s on TV tonight’?

Following up on the previous one. Having laid out the content value chain, I pointed to the demand side indication that – availability of content has made discovery a problem worth solving. A quick glance at each of them below.

Content Creation

Premium content makers like Disney and Discovery Communications have taken a leap towards Direct to Consumer (D2C) initiatives. Disney launched DisneyLife in UK for £9.99 per month in Q4 2015, planning to expand in rest of Europe in 2016. Discovery Communication announced launch of its premium OTT service in Denmark, Sweden & Italy. For studios, the primary source of revenue is licensing. The portal page for an app like Disney’s D2C offering focuses on Disney characters (instead of movie titles) like top selling franchises a.k.a Frozen. Recommendation will help user stickiness, but the target audience here doesn’t care much about discovery. The incentive to reduce churn on a subscription service via recommendations isn’t strong enough (yet).

Subscription VOD (SVoD) players like Netflix and Amazon are investing in creating their own original content. Revenues are driven by ‘subscription’ (needless to say).  SVoD players can benefit consumers by offering a recommendation solution, helping them make a choice from a diverse catalogue. A far more powerful tool for these players is analytics, to ensure they remain ahead of the curve in monitoring consumer preferences which has a strong bearing on investments in original content. A good recommendation system will drive user experience and user stickiness (an indirect $ impact) for an SVoD player. Improved content discovery will quicken the feedback loop. However from a consumer perspective – he will get all these niceties in the wall-garden of these individual services. An SVoD player will be far from being able to leverage all the hooks in the user journey of content consumption.

The other extreme of the spectrum has independent artists and freelancers, creating niche content for targeted audience. They work either with multi-channel networks (MCNs) to reach a large viewer base or themselves manage their creation on the usual suspects – YouTube, VEVO and others. These are typically ad-supported models. With little resources of their own, independent artists rely on the content aggregators to improve the discovery experience.

Content Aggregation & Distribution

In this seemingly infinite pool of content, next in line are content aggregators & distributors. (Telco) Operators & PayTV providers have their own managed networks (read ‘walled gardens’) distributing content (in the form of channels) to consumers through varied media (satellite/cable/terContentDistributorrestrial). Bundled subscriptions have been the norm till date – putting together a mix of highly desirable and nice-to-have channels together. The likes to Sling TV however have started to disrupt this arena – leading to ‘skinny’ bundles. Triple/Quad/’you-name-it’ Play from the telcos – mixing the phone, the internet and PayTV package together – are yet another way to earn revenues and reduce churn. Certain operators also benefit from government subsidies/grants and government imposed license fees to fund these operations.  From the Operators & PayTV providers kitchen, till date the (Electronic) Program Guide (EPG) has been the recipe to help users make choices. PayTV providers have also started playing with non-linear sources and the EPG fails the litmus test here. A good recommendation system will drive user stickiness for the operator reducing churn.

OTT providers are the other open-internet based content distributors. Transaction VoD (TVoD) players (like Maxdome, Videoland in Europe) rely on licensing arrangements with content owners and earn their revenues through a transactional (pay per view) model. TVoD players strongly benefit from a search & recommendations solution, giving users an improved discovery solution, thereby directly influencing revenues. However the TVoD service will compete for viewer’s attention against SVoD services, cable subscription and other content sources.

Content Consumption

And lastly – the point of consumption – a massive television in the living room or a compact handheld device. It could also one of many media streaming devices connected to TVs (the Chromecast, Roku, Apple TVs, Fire TV and others) that give users access to the world of content. Device makers primarily make money through one time device sales. Transitioning from a product-only business model to product/service oriented business model, device makers now aim for a share of revenues from content service partner subscriptions acquired through their devices. For a media-streaming device maker, a similar rationale applies like that for TVoD players.

A good recommendation system, means increased user engagement, which in turns equals higher traffic on non-linear content through the device in the hope of new subscriptions originating from it. All of this would mean increased ancillary revenues on top of device sales.

For this consumer though, his linear-TV consumption habit does not get captured when recommending a movie or program from his catalogue on the media-streamer. Likewise TV maker, can have a positive impact on the ancillary revenue, however more importantly the consumer could get an integrated experience. The different kind of sources connected to the TV – USB, set top box, media streamer, dvd player, built in OTT Apps – can give the TV maker that ability to  know what kind of content the user watches across these sources.

The final word – All for one, one for all!

OTT services installed on the TV, linear viewing habits from broadcast, on-demand content consumption patterns – all of these could act as inputs to a recommendation system, giving a better understanding of user preferences. Taking a wild-step ahead, if the industry players decide to drop the wall, they could potentially benefit from knowing the user behaviour in the other’s world (OTT players will know what linear TV  viewers are watching, and the other way around). Industry players & analysts already start to recognize these barriers. Gaining this insight will help up-stream players streamline their own content portfolio. Industry leaders in this space would perhaps not want to do this approach (after all a Netflix viewer for example, spends effort to find the Netflix icon and browse through its catalogue), however tier 2 & tier 3 players and the challengers in both these content worlds would stand to benefit from this standardized approach, with the possibility of overall increase in user engagement and revenues.

What’s on TV tonight?

What’s on TV tonight?

That is  a million dollar question. Unless if you are extremely opinionated on what you like to watch!

The internet and other rapidly evolving technologies have drastically lowered the barriers of content creation and distribution. This has resulted in an explosion of content for consumption. Content creators like Studios now compete with likes of Netflix and niche artists on YouTube channels. Users have a plethora of content to choose from & a variety of platforms to watch it on.

Content Value Chain

Trying to answer, “What’s on TV now?” has become increasingly difficult. Breaking down the content journey into a value chain can look something like below

The Content Value Chain

Industry players attempt to simplify content discovery, hoping to drive user adoption. Search & Recommendations is the holy-grail of content discovery. But, in the content value chain, every participant is active in this dpace. How can they drive user adoption? Are industry players willing to go beyond walled-gardens? Is any one of them better positioned than others to create enough value for the user, while capturing enough value for all participants of the value chain?

What is the goal of having a content recommendation system? Depending on where one sits in this chain, it could either be to make money or could be to boast of incredible user experience indirectly creating brand affinity.

Exploring further, I attempt to outline the players involved in the content transformation phase, figure out what their incentives are to build/buy a recommender system and how do such propositions impact their business model? Let’s start from the right extreme – the demand side. When it comes to content consumption, the end user is the king here.

The end user (Content Consumption)

A study from Digitalsmiths (Survey demographics covers North America) shows increasing difficulty in finding content that users really ‘want to watch’ (see adjoining figure here)

Complexity with content discovery
Is it easy to discovery content?

The number of programs users can find is extremely high. To make a decision on what they should watch is tedious.

An excerpt from an article states, “For pay TV operators, the challenge could be as simple as people just can’t find what they’re looking for. According to Digitalsmiths, 71% say they get frustrated because they can’t find something for the family to watch. Nearly half of pay TV customers don’t use search, saying it takes too long (20%) and is just too difficult to find (18%.)”

Users have no time to browse through the content clutter. Yet another barrier is the user experience. Depending on the type of device the user consumes video content, he expects a different kind of interaction paradigm – each suited for that device type.  (Reminds me of the famous Ted Talk from Barry Schwartz – The Paradox of Choice). So the consumer is thinking either of watching something that is popular among the masses (hence in the first handful of installed channels) or just watches a show based on word-of-mouth referral. That he has a certain taste & preference has little bearing on his viewing habits.

Who should empower this user? Is the content creator, the content aggregator or the TV device maker best placed to fulfil all objectives and deliver the punch?

More to follow, in the next post…

Should the TV Guide still be ‘yet another application’?

Should the TV Guide still be yet another application?

After two back to back events, IFA at Berlin and IBC at Amsterdam, its finally good to get back home. These are two places where you would expect a lot to happen in the consumer electronics space and the closely related content-space. I took the opportunity to attend a few conferences this time at IBC and an interesting one of them was titled “From EPG to PPG”. Eminent panelists presented and discussed their views and I took the opportunity to get inspired an jot down a few thoughts.

How old is the TV guide? Any guesses?

Program guides a.k.a TV Guides have been around since as early as 1940’s, albeit in the ‘printed format’. The electronic version (EPG) has been around since early 1980s in North America. As per Wiki, Western Europe still took some time to adopt to the EPG (early 2000). Not much has changed in the EPG over all these years. It still is the matrix, rows full of program names mapped against time of the day and day of week.

So, what does the TV guide do for the consumer? What is the job done?

To take a step back and think – what problem does the TV guide solve?

“It helps viewers make choices. Which program or movie should I watch next or even watch later in the evening – that’s what the TV guide tells me”

TV guides in all these years have presented viewers with a list of programs. While the viewer is watching a TV show, at the end of it he opens this one application, hunts around for the next show he wants to watch on the same or other channel – and Zap! There he goes, switches to the next program with his pop-corn! With all the clunky interfaces and the evolution of catch-up-TV services, some operators took a step further – they let viewers ‘go back in time’ on this TV guide. Viewers could now discover and play back previous missed episodes from this interface.

What are the alternatives today?

A lot of debate and discussion of course focusses around the emergence of OTT content consumption vs. linear TV viewing experience. A report from Juniper Research suggests that subscriptions from ‘over-the-top’ (OTT) TV providers such as Netflix and Amazon Prime will generate $31.6 billion by 2019, up from just under $8 billion in 2014. How do these services present their content to viewers? Recommendations – is one of the primary means to achieving this. To draw an analogy, remember when buying books (or any items) on the Amazon website, you are prompted “You bought this, so you might like that..” … a cool way of understanding your preferences, mapping it with the inventory on offer and creating a opportunity to up-sell goods and get a larger share of the wallet.

A similar mechanism exists in the content space, albeit with the objective of ‘keeping you entertained with stuff you want to watch’! And that is called Recommendations. So, while the scope of content is different (it is on-demand content) the job being done is the same – helping the viewer make a choice.

What should the Next-Gen TV Guide look like?

During this conference, Brenda O’Connell from Twitter opened her presentation with a bold statement – ‘The EPG experience is broken today’. Taking a user away from his current viewing, making him navigate through a myriad of program names, hoping he would select the content ‘almost’ right for him, reading more about it on the screen and if all looks good, lo behold he switches channels to actually start watching. Can nothing be done to throw this experience out of the window and look for a new way of getting the job done?

To steal a phrase from yet another speaker at this panel discussion, Fabian Birgfeld, the next generation TV guide should give a ‘Cinematic Integrated Experience’. Rather than the make the user open this one application to see a grid of program names and time, the next generation experience on TV guide can be derived from this ‘recommendation experience’. (See a beautiful illustration at http://bit.ly/1SZfn64 starting from timestamp: 18m16s)

Right before the end of a program, an end-screen notification pop-up indicating a ‘personalized and recommended’ program coming up on any channel. While a viewer is presented this choice, it can be reinforced with ‘why this is best for you’? Using genre and semantic based keywords can convince a viewer on the choice of program he is about to make. Overlaid recommendations and program information will enrich the viewer experience making it easy for him to flow through content. It could extend to mood based recommendations and even event based choices localized and personalized.

In all this scenario, the second screen device also can play a significant role. Multi-user login is still a tough nut to crack in the TV space. Proximity detection enabling viewer identification can help figure who is sitting on the couch in front thereby helping the cause of personalization.

What are the challenges in achieving this?

  • Broadcasters love their real-estate. Content rolled out by some broadcasters has a ‘watch next’ overlaid on the video feed. Additionally brands pay for the advertisements. Neither broadcasters, not those brands would like an atrocious overlay on top of their content. More so if it results in taking the viewer away from the channel there will certainly be some displeasure. After all ‘eye balls’ is what the media industry cares about. Having said that, broadcasters will be able to benefit from viewer data and make better decisions around content and advertisement. They will be able to leverage this towards monetising better targeted advertising.
  • Will they ‘All’ participate? In addition to this Pay TV bundle, will the OTT players play along. The business model of OTT providers has started to depend on original content and latest content release window (from tVoD providers). Rightfully so, they favour their walled-gardens. It helps them better understand consumer needs, thereby helping the investment decision-making process. If these players open up their catalogue interfaces to TV makers and Pay TV operators alike, this content will become a part of the broader mix! Will it loose its premium position? Not necessarily. As they are invested in quality content creation, their content where relevant will be stay afloat over the rest in the recommendations.
  • The consumer question ‘Will my TV give me this experience or will it be the set-top-box?’  Amongst this install base, different geographic markets have different adoption ratios of linear viewing through the TV vs through a set-top-box. Only the former part of this install base will use the TV guide on the TV. Is this base big enough for TV makers to spend money on? Does the meta-data and the powerful recommendations algorithm behind it have sufficient business value to the TV maker? On the other hand, using the set-top-box keeps the experience under the control of the operator – the gatekeeper to the viewer’s linear content.

A transition in the user experience paradigm from this grid view to an integrated experience will create a leanback viewing experience. Certainly more than one player in the value chain will have to work together to bring this dream to a reality.  For the viewer the new ‘personalized’ TV guide will be more of a personal TV assistant than a mere two-dimensional application.