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User experienced

Universal discovery has long been an industry goal, but will the scale and complexity of content always keep a global solution out of reach? Adrian Pennington reports.

Consumers can’t be expected to know everything that’s available to them in the vast pool of content in the world. They need help and the service that does that best will be well on its way to success. Since discovery comes in many forms, from accidental to recommended, and a million things in-between, the next frontier for broadcasters and operators in this area is about making sure consumers can view what they want irrespective of where that content is coming from.

Unified or universal search and discovery has been an industry aim for a number of years but the need for it has increased recently as more and more of us view content from on-demand and streaming sources alongside and often in preference to linear broadcasting.

“Being able to do this in a simple and holistic way really solidifies the need for new technologies such as conversational voice and personalised recommendation systems,” says TiVo’s senior director,  international marketing, Charles Dawes. Unified discovery is deemed critical if the industry is going to keep on delivering the content that consumers desire. Dawes says: “Consumers don’t know, and shouldn’t need to know, where the source of their content is. They don’t need to understand terms like linear, DVB, IP, broadcast and OTT when all they want is to enjoy their favourite video on demand.”

Universal search and discovery breaks down the walls between TV providers making content more easily findable and watchable. Laurent Van Tornhout, vice-president, product and marketing at Zappware says the goal is “full integration in one UI experience and multisource – aka universal – search.”

Such a goal moves beyond basic search. “Going beyond basic genre and delving into dimensions of content such as mood, theme, setting and character attributes [means] a new generation of navigation and recommendation offerings will suggest the TV shows and movies most likely to resonate with individual viewers,” says Simon Adams, chief product officer at Gracenote.

Further, cross-media content discovery will enable viewers to find and watch music videos on TV or identify musicians or athletes in movies. Gracenote’s datasets and Gracenote IDs, which enable universal search across different platforms, services and content types could be key to this.

In parallel, short-form and user-generated content is on the rise and equally relevant as content choices. “Even long-form content is being chewed up and spat out as bite-sized chunks for the more ‘attention challenged’ viewers,” observes Anthony Smith-Chaigneau, senior director, product marketing, Nagra. “Shows and movies have endless amounts of related video content that are accessible to fans. Looking at just the explosion of gaming and the massive online following of Twitch users, Instagram influencers and Facebook video content that is competing for one’s time, you realise that content discovery solutions of the future will have to evolve to not only provide access to alternative content but may be driven by it.”

Value of universal search

Universal search should allow the viewer to fully understand where a particular piece of content is, how much it costs and whether they have access to it with their existing setup. Yet the current trajectory of content silos “make global search and discovery difficult”, says Smith-Chaigneau. “Having a source- and service-agnostic way to remove those ambiguous groupings addresses the real pain point that needs to be addressed. There is no Google for TV in the mainstream although many are trying to be this.”

If there were, the value of intuitive navigation and universal discovery, which is already “sky high” says Adams, “would go even higher”.

“User-centricity would bring added value for the telecom operator as the content aggregator for all sources of content,” agrees Van Tornhout. “For the consumer, the value is that, done right, their experience is simpler and seamless – meaning they spend more time enjoying content rather than searching for it.”

Unified search and discovery could bring the operator “a wealth of new opportunities”, says Dawes, that are built around a foundation of having a connected, engaged consumer who doesn’t need to go ‘off platform’ for their content. Dawes continues: “Operators have long known that giving access to all the content the consumers desire via their remote – aka their ‘brand in the hand’ – is key for their business and helping consumers understand the value they bring.”

Simon Leadlay, director, pay TV business development at You.i TV highlights the relative poverty of experience for most broadcast sports fans. “Broadcast TV still scores highly among sports viewers. Yet the discovery UI found in most pay TV services doesn’t cater well to that market,” he says. “I would expect a huge potential for subscriber stickiness and satisfaction for an operator to combine traditional sports video broadcasting with a plethora of on-demand and OTT sports entertainment news, stats, team information, and replays of past games and special events. Sports fans are finding some of this rich experience via direct-to-consumer platforms  by their favourite leagues, but very few have a similar offering available from their operator. There’s a lot of room for improvement here.”

According to Leadlay, the best kind of discovery systems should be quietly knowledgeable, unobtrusive, and yet always recommending something. “At the same time, I am personally worried about the risk of over-recommendation: where I’m never offered anything new, fresh, or out of my comfort zone,” he says. “I think it’s important to strike the right balance between seeing familiar and new content.”

Leadley suggests that the next frontier is likely to see “increased commoditisation of what advanced recommendation and discovery systems are already using”, namely more machine learning to drive truly individual recommendations based on time of day, location, device, and previous activity.

If it’s agreed that the system would need to know who the viewer is and understand the individual’s likes and dislikes, then ‘discovery applications’ would have to be redesigned. Smith-Chaigneau says: “All of the streaming video services are currently obviously inadequate in coping with the sheer volume of content available. Everything seems to be a Netflix clone. The technologies driving the content like recommendation engines will also have to be redesigned to be more sophisticated. Even how we ‘think of content’ will have to evolve for us to come up with the right solution for the future TV watcher.”

Recommendations made to an individual could be increased in relevance by adding profiling input from other online sources. This can happen “provided that the back-office of different online systems can feed each other technically as well as from an opt-in point of view by the end-user,” points out Van Tornhout. “In terms of personalisation you’d need to bring the most relevant content and content suggestions based on profiling, context and device used at that moment by that user. The service would also need to aggregate different content sources to be able to bring the ‘fat tail’ as well as the ‘long-tail.’”

Vendors began embracing the need for universal discovery across the consumer electronics and operator spaces a while ago. Tivo, for example, lays claim to being the first user experience provider to integrate Netflix into an operator when it helped Virgin Media launch the streamer in 2013.

Zappware’s Nexx 4.0 UI promises personalised content on any screen

“For operators there was a need to bring unified discovery to their platforms even before the current trend of adding in multiple video content sources,” says Dawes. “Tivo now integrates multiple video sources into a single experience that is led by the content rather than the service the content comes from. When a consumer searches for their favourite show they are presented with the show first and where to get it from second.”

Gracenote’s global video data offering is built on a unified data schema “that provides a consistent and standardised format for all international data,” says Adams. The Nielsen-owned firm is also developing the next generation of descriptive metadata and images in its Advanced Discovery suite. “These solutions help providers deploy all-new personalised recommendation capabilities, visually rich guides and even voice-driven experiences,” he explains.

AI and metadata building blocks

The second phase of unified discovery will make greater use of metadata powered by machine learning tools. “Metadata is absolutely critical when you are delivering a compelling discovery experience,” Dawes says. “It is no longer good enough to have the simple time, title and channel that some EPGs deliver. Today’s discovery systems, especially those which are voice driven, need to have a high-quality baseline of information about each piece of content.”

Tivo refer to this as the ‘Metadata iceberg’ where a small amount of visible data is underpinned by a huge amount of non-visible information. Sitting on top of the metadata is a personalised recommendation platform. This goes above and beyond a simple rules-based recommendation system into a system that can be personalised based on time, day, context and an innate understanding of how individuals personally consume content.

“Access to a wider range of metadata that allows users to pivot from content to content is essential to providing a rich expansive experience,” says Nagra’s Smith-Chaigneau. “However, if you look at Netflix, it puts tremendous effort into creating its own metadata and manipulating it accordingly. For example, it has shown that different users are drawn to different types of movie posters. Users on the Netflix platform see different movie posters based on their previous viewing habits, whether they have binge watched, and other parameters discovered by the system.

There is also the concept of dynamic metadata which goes beyond static images of posters and actors. But the constantly changing social commentary and related media content is also becoming an important facet to the primary video. There will also be frame and scene content tagging for age appropriate viewing which all highlights the importance of metadata.”

Enabling anything from poster quality, size and colour to clear and well-crafted information that ensures any and all platforms can present it for viewers to effortlessly discover and consume is an increasingly complex task but metadata is foundational.

“As the world of content merges there are now exceptional foreign titles found in the mix so there are language issues to overcome, translation, subtitling and a whole swathe of cultural aspects that also need to be taken into consideration,” observes Smith-Chaigneau.

Artificial intelligence and machine learning are increasingly playing a greater and greater role in automatically building out content metadata, be it from assessing and assigning a confidence level when information is initially imported, through to keeping tabs on how the importance of relationships between different pieces of content changes over time.

“AI-assisted metadata will soon become the norm,” says Smith-Chaigneau. “AI can afford more depth to metadata services where it could, for example, compare the synopses of two titles and identify differences that could then aid or automate editorial management of those pieces of content.”

With more and more user data points available and with much more sophisticated methods of interrogating it, “we have to evolve past simple usage-based recommendations toward hyper-personalisation,” Smith-Chaigneau says. He suggests leveraging social indicators and ML to better understand what drives users to content “especially as the experience crosses over into more and more personal devices, with unique behaviours.”

On top of all this, there’s a clear trend toward a voice-based discovery model. The sheer scale of available content renders the tools of the linear world, such as a grid or tree-based content catalogues, insufficient going forward.

“Voice input frees you from the limitations of single character entry and allows you to discover content in the way you think about content,” remarks Dawes. “The system should be able to respond to simply saying ‘What’s on TV tonight?’ and put together complex queries like ‘What’s the film with Peggy from EastEnders and Kenneth Williams?’. It should ‘know’ you implied ‘for me’ and give you a set of personalised results from across your entertainment choices that isn’t limited by linear TV.”

TiVo is a leader in voice-based discovery

The user interface, of course, shouldn’t be the destination for the user; that should be the video content. However, as Leadlay underlines, a great user interface can make the process of finding and watching that content truly satisfying, “and we all know that a poor user interface leads to frustration and failure.”

Ideally, the simpler the UI, the better. It should be intuitive, get you to where you want to go in the least number of clicks and to all intents and purpose be transparent to the user. Arguably no-one has yet alighted on the absolutely right design mix.

UI as entertainment brand

“It is sometimes hard to break the mould of consumers’ TV UI habits – removing the EPG proved to be wrong for some platforms who soon added it back to the mix,” says Smith-Chaigneau. “Not having channel numbers also proved to be a no-no for one European platform which had to rapidly add them back in because a lot of viewers had become used to that form of navigating. We have tried 3D UIs and other fancy tricks but, just like PowerPoint, all the fancy fonts and animations simply interfere with the objective of getting the message across.”

The industry has experimented with many different discovery mechanisms from personalised to promotional, curated, edited, serendipitous, trending and logical recommendations. It has incorporated cognitive search and voice options and now it is incorporating AI in the background.

“We blend all of these together and try to create a simple and refined way of presenting these in visual form so the consumer feels they are being well served. From a product design standpoint, the necessity to have a connected platform and flexibility across platforms is the most interesting tool. We have to think of our products holistically and as complementary parts of an ecosystem. We have to leverage more distributed tools and standardised development libraries,” says Smith-Chaigneau.

In general, it’s difficult for the UI or UX to be the entertainment brand by itself. The experience is reliant on the content and usually it is those content brands which are seen as the entertainment brands by consumers.

However, you could argue, as Dawes does, that ‘TiVo Experience 4’ is one of the few entertainment experience brands that exists in its own right.  “As an established consumer platform in the US, with a loyal customer base, TiVo has won multiple awards and been featured in popular culture on many occasions. Consumers choose TiVo for its extensive functionality, continued innovation and ability to get your key entertainment choices in one place, be they linear or streaming services like Netflix,” he says.

Zappware’s Van Tornhout agrees that if the ergonomics are right “and if relevant enough for the end-user as a gateway to discover all the relevant content across content sources” then the UI could become an entertainment brand. “The UI should be grandma-proof as well as millennial-proof.”

It’s arguable too that some of the latest OTT services view the UI as an integral part of their package and branding. Disney will surely look to create such a UI as its brand is already synonymous with entertainment, as opposed to a service provider that delivers multiple entertainment brands in a single UI.

“Just as Google became the brand of internet search, there is definitely an opportunity to be the face of content discovery,” says Smith-Chaigneau. “There is a magical blend of form and function that, when applied to obvious pain points, can become ubiquitous.”

In focus: Curated or algorithim-based discovery?

While the sophistication of algorithms will only get better, editorial or curated discovery will retain a role in the creation of a ‘more human-led’ approach to any service.

“One of the drawbacks of early recommendation systems that just relied on techniques such as collaborative filtering was that they would drive you further and further down an ever-narrowing set of content choices,” says Tivo’s senior director of international marketing, Charles Dawes. “There was no facility for companies to promote content that was important to them commercially or for the system to understand the difference between a customer needing to watch something they like right now or them looking to broaden their content horizons.” TiVo says its Personalised Content Discovery platform has the ability to blend not only editorial and algorithmically-based recommendations and predictions but also include new recommendation paradigms such as sponsored discovery – where paid placements are served to the right, receptive consumer. “This will deliver a superior experience that enables more video viewing than ever before,” Dawes claims.

It is the vast amount of legacy content in addition to new content that presents the real challenge of scale to manual processes. “By leveraging both human editors and ML, we’re able to create datasets with the breadth to cover existing and new content and the depth to describe that content with increasing specificity,” says Simon Adams, chief product officer at Gracenote. “This is critical to positive user experiences.”

“We know that there’s a need to go beyond editorial and algorithmic recommendations, using AI to better predict not just the type of content, but getting to why we ultimately watch what we do,” says Anthony Smith-Chaigneau, senior director, product marketing, Nagra.

There will be a blend and balance of the two recommendation forms. For example, says Laurent Van Tornhout, VP, product and marketing, Zappware the first three items could be editorial, related to a trending topic, and the rest of the suggested items on the ‘bookshelf’ could be algorithm-based.

Nagra’s Smith-Chaigneau says: “I will never forget talking to an Uber driver about his TV consumption and he said that after about six months of using a particular OTT service he went home after a shift and realised how boring and same-same his TV viewing had become. The machine had led him down a silo of similarity and he was bored with what was on offer to him. He wanted a reset-button so that he could flush out the system and start all over.”