Solving European Broadcasters’ Pain Points with Softserve

MTM and SoftServe recently published a white paper that explores broadcasters’ core challenges in the European market, and considers how innovative technologies can help them thrive. This mailer provides a taster of the core findings from the white paper.

The European TV Market is growing, but broadcasters must innovate to compete

Western European TV revenues are growing, rising from $39 billion in 2017 to an estimated $50 billion by 2023. Executives argue we are in the ‘Golden Age of Content’, with broadcasters experimenting with new formats in multiple languages, with successes including Killing Eve, Broadchurch, Deutschland ’83, The Bridge, and Spiral.

However, as is well known, the landscape is changing and European broadcasters need to innovate to compete. One core area is artificial intelligence (AI) – the ability of a machine to perform cognitive functions we associate with the human mind through processing large volumes of data.

Here are our top three findings from our whitepaper exploring the impact AI can have on the video value chain:

1) Content creation is difficult in a multiplatform, ultra-high definition world

Creating great content is what drives user acquisition and retention. However, more hours of TV content are being produced on a greater scale than ever before, and the battle between Netflix, Amazon, pay-TV companies and US entertainment giants is intensifying. For example, Amazon’s investment in The Lord the Rings television series has an estimated cost of almost $1bn, including rights and production costs, with a cost-per-hour of almost $20m. This price inflation places pressure on broadcasters with new demands and complexities around producing compelling content, particularly for live events such as sports.

Recent developments in AI have tackled these problems by applying advanced solutions to unstructured data sets, or creating advanced robotics to solve production challenges.

By employing technologies in this way, broadcasters and content producers can create new efficiencies in the production process. One example is in tennis, where an on-court statistician creates highlights packages without the need for editors to spend hours sifting through game footage. Instead, the AI system determines important moments like break points, the length of rallies and ball speed, as well as automatic cameras that follow the action and record the roar of crowds or erratic player movement to determine pivotal points.

2) Content management is key to successfully delivering across multiple devices

Content management – the process of transferring, re-versioning, localising, transcoding, and sharing content – is becoming ever-more complex for broadcasters. With multiple organisations responsible for different segments in the value chain, ensuring consistency in content management and versioning is increasingly a challenge.

Developing a deep understanding of content through automated metadata tagging a term for individual pieces of information about digital files, is front of mind for media executives. Rich metadata about content broadcasters create (or distribute) provides executives with the opportunity to extract maximum value from prized content assets. For example, metadata applied to content archives means users or producers can quickly search for previous programmes with a specific actor or scenes filmed in a specific location.  

3) Content monetisation requires accurate data about the content and its consumption

Metadata can also be employed effectively in monetising content. Media executives are increasingly interested in advanced advertising (combining ad inventory and data). With advertisers buying advertising digitally, there are opportunities for AI supported systems to apply metadata to the advertising process, track impressions, and provide real value for advertisers and agencies through sophisticated demographic targeting.

Furthermore, AI can be applied by intelligently looking at the environment in which ads are served, or even through facial recognition technology to determine responses from consumers. This means broadcasters can understand who the customer is, where they are and what they are watching in order to serve them the correct ad at the right time (and in an environment complementary to a brand’s identity).

To compete with digital giants, broadcasters need technology partners

The growing complexity of the video value chain places new demands on broadcasters, who are typically managing both legacy distribution technology and new IP-based platforms. To respond to both the challenges and opportunities, executives are increasingly relying on partnering with technology vendors as building flexible and agile solutions in-house is considered expensive and challenging.

Finding these partners is crucial, and they must possess three core qualities: i) Credibility – through data, results or evidences solutions; ii) Specificity – specify exact problems rather than optimise across a wide range of areas; and finally iii) Inclusivity – communicate processes and solutions to clients without obfuscation.

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If you would like to talk more about artificial intelligence and its impact on broadcasters, please do not hesitate to get in touch.