A Ooyala user interface.
According to the most recent Ericsson Mobile Report, UK viewers now watch over a billion minutes of TV content online per week. With the likes of Netflix and Amazon Prime investing enormous amounts of budget in original and exclusive content – not to mention the online content licensing that’s needed alongside it – the streaming services industry has quickly become a content arms race, with those with the biggest budgets often coming out on top. For smaller content producers, this means having to invest in the speed and efficiency of their content supply chains sooner rather than later. The key to Netflix’s success – perhaps surprisingly, above even its famed user experience - has been its own unique supply chain. This supply chain ensures that every piece of content published on the site, including those targeted at regional and niche demographics, is more likely to be a hit than a miss. By effectively utilising the data in the supply chain, content producers will have a better understanding of both the cost of production and of which audiences are engaging with what content so that they can react accordingly. Visibility into these data sets means that businesses can effectively calculate their return on investment in content production without taking as many risks – provided the right technology is in place to do so.
Understanding the workflow
As the amount of original content continues to soar, a growing number of distributors have less patience when it comes to waiting for shows to build an audience and this means shake-outs for shows experiencing a “bad month”. In order to combat any lulls in content in this instance, content producers must implement a media asset management system and some form of an archive.
If that system is working effectively for the content product – which is rarely the case – and there is a central repository of assets operating across the entire organisation, it means that they have quicker access to old content that can be reused at a moment’s notice, much to the delight of any content distributor in want.
Once those initial efficiencies have been put in place and existing content is no longer being recreated, the next step is building out the workflow from that core and connecting all the systems and processes. Then content producers can really start to accelerate efficiencies by automating tasks previously undertaken by humans with artificial intelligence plug-ins.
Automate to assimilate
Automation is transforming every aspect of our day-to-day lives, and the media and entertainment industry is no exception. Here, capabilities can be multiplied, and on the same budget, to allow content producers to better target niche markets around the world. By automating a tedious and traditionally manually-driven process, content producers can knock as much as 90% off of the time taken to recognise a piece of content.
Investment in AI and automation has become imperative for any content producers wanting to measure the appeal of their content to a new demographic before investing mammoth amounts of money – particularly now that audiences are more fragmented, and producers have to store more metadata because more content is localised for more regions.
In a rapidly evolving landscape, its vital that producers can keep pace with new technologies that are transforming the way people consumer their content. Virtual reality and 360-video are just some of the forms of content that content producers are keeping a close eye on. However, if producers don’t have the supply chain in place that allows them to make it easy to test the relevance of new formats and technologies for their audiences and processes, they risk falling behind.
A recent Digital TV Research report predicted revenues for TV shows and movies delivered online for the top 138 countries will hit $83 billion in 2022, more than double its value two years ago. For content producers wanting a piece of the pie, its time to streamline the content production process through an effectively media platform to ultimately move through their supply chain more quickly, efficiently, while generating more meaningful data along the way.
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