Every year, Accenture publishes a report titled The Future of Broadcasting which analyses the trends and technologies on the broadcast industry roadmap. In 2016 it noted that market expectations in the industry had soared, and in the 2017 report, The Future of Broadcasting V, it asked where the growth was going to come from to justify the lofty future values. And Personalized TV is a big part of that.
It identified four key industry themes:
- Investment in content production
- M&A activity in a bid to achieve scale
- The growth of direct to consumer offerings
- The establishment of OTT services that complimented existing linear ones.
And it examined three opportunities for value creation in response to that: how to capitalize on service as a point of differentiation; how data analytics can be used as a strategic tool for content decisions; and how incumbent broadcasters can exploit the “broadcast advantage.”
We would argue that data analytics, and the Personalized TV it helps produce, in particular, has a lofty role itself in all of that. Which is why we've made it such an important part of the latest version of our VO TVaaS cloud-based television solution.
Here’s a soundbite from Sky Media Deputy Managing Director, Jamie West, speaking at a Royal Television Society event in the UK last year (and yes, the UK does have a royal TV society…)
“Personalization runs all the way through our business from the call centre, to commissioning, to advertising.”
Data is Increasing Exponentially
We first wrote about this last year when we pointed out that there is going to be a massive increase in the velocity, volume and variety of data in the very near future. The full article is here, but it’s worth a quick recap.
Essentially we are going from a recent past where data rates were around 500kb per household per month and all that was being collected was information gleaned from clicks on the remote control, to one where the amount generated per household is likely to top 500MB per month and what is being collected is, well, pretty much everything to do with TV viewing. Who is watching, what device they are watching on, perhaps even what else they are doing at the same time and, if VR takes off the way it could, exactly what part of the image they are watching too and a whole lot more.
More than that, the data is then being collated with other data sets. What the weather was like at postcode level at the time, what the major news stories of the day were, perhaps even mood gleaned from an analysis of keywords used in social media postings.
It is interesting to note that there is a boundary line in those two paragraphs, a point where personalized data tips over from being fascinating and useful to vaguely Orwellian and uncomfortable, and this is a path that operators and miners of Big Data are going to have to tread very carefully in the future. Legislators will be watching carefully and public opinion may turn volatile on the issue, especially when people realise the value of their data to companies.
From Personal Data to Personalized TV
There is some disagreement in the role that Big Data has played in recent years, particularly in regard to Netflix. The standard take is that Netflix uses analytics to deeply understand consumer preference and commissions shows such as House of Cards as a result. Others disagree with the scale of this analysis. Speaking at the RTS Big Data event, Pedro Cosa Fernández, UK broadcaster Channel 4’s Deputy Head of Analytics, reckoned Netflix uses data “more for validation than [content] creation. It knows its customer base and it can validate its investment and look at the potential of acquiring content.”
As the RTS review of the event continues, however: “Programme-makers, he added, understand that using big data to inform content “is going to be big in the future”, but currently it is used more in scheduling than for taking creative decisions.”
No one really knows how Netflix uses its data and when it says a show has been a hit what it means by that. Its figures are never released. Certainly though, by a range of third-party metrics, from critical acclaim to social media analysis, it has produced an impressive amount of original popular shows, and it would be quixotic to insist that analytics played no part in that process whatsoever.
As we concluded at the end of The New Life of Operators’ Data: From Big Data to Bigger Data, Big Data is indeed growing into Bigger Data, and Even Bigger Data is on the near horizon. How will broadcasters and operators deal with that tsunami of information? What sort of issues will emerge as privacy concerns and the growing realization amongst audiences regarding the value of their data start to become publicly discussed? And what changes need to be implemented within organisations to make the most of the new personalized TV that results from capturing information on such an impressively granular level.
Establishing an integrated analytics strategy is an important part of the future. As Accenture puts it in its own conclusion: “A siloed approach to analytics will not lead to an improved return on content investments.”