Data and TV: The importance of analytical insight in modern broadcasting

The world is becoming more connected by the day.

If Gartner’s estimates are anything to go by, there will be more than 25 billion devices hooked up to the internet by 2020, up from ‘just’ five billion today. The main side-effect of this evolution is big data - or enormous data, as it probably should be known.

The stats are pretty substantial here too. According to IBM, there’s currently around 2.7 zettabytes of data in the digital universe, but by 2020 we’ll be generating 35 zettabytes every year. Much of this information is valuable. It helps organisations from all sectors make better, more informed decisions about how they operate. Thanks to the rise of internet-connected TV, the broadcast industry is no different.

Data from everywhere

People now watch TV in a number of different ways. You have the traditional linear broadcasting most commonly found on conventional living-room sets, now supplemented by branded mobile applications and browser-based channels. All of this viewing activity generates data, which tells us what people are watching and how they’re going about it. In isolation, a lot of this information will be pretty useless, but bring it all together and new doors begin to open.

In the past, content owners would pump content out without really knowing what happened to it afterwards; any insight thereon was lacking in real accuracy. Now we have access to so much information, however, we can shun the extrapolated surveys and analyse to our hearts’ content. The result is an opportunity for broadcasters to dramatically improve the way they develop and distribute content.

Different types of data

Firstly, you have basic reporting data. Much like that you’d find on a normal website analytics tool, it includes things like the number of viewers, unique viewers, time spent watching etc. From here you can start to highlight spikes and drops in audience size, and work out exactly how well a channel (and its content) is performing over time. This kind of insight might be used to optimise programming schedules, or it could play a part in advertising deals.

Then you have the technical side of things to consider: operational analytics. Much of the data that comes in will relate to service quality, so things like loading times, drops in packets and crashes etc. – basically anything that negatively affect the consumer. Only when you see this can you start fixing it to ensure the best possible viewing experience and increase consumption. When it’s possible to identify issues early, content owners have the chance to address them before they prevent people from watching altogether, thus increasing customer satisfaction.

Beyond this, there’s the more in-depth customer insight. This might focus on a viewer’s activity and behaviour within a branded app or web page – how long they spend reading program descriptions, or the points at which they skip adverts, perhaps. If, for example, you can see that most viewers exit the app halfway through a minute-long promotional clip, it gives you the chance to reassess your approach to advertising.

In simple terms, data has the power to highlight problems and opportunities for improvement, allowing content owners to take action and either fix or capitalise as necessary.

Instant analytics

Traditionally, understanding of a show’s demographics and success would come through traditional market research techniques like surveys and focus groups, but it’s a flawed approach. For one, the data would be collected on a small scale and then extrapolated to generate larger figures that are ‘relevant’ to the rest of the country, making it pretty inaccurate. More than this, though, there’s a delay; you have to wait for information to be gathered and processed before it can be used.

Today, with the rise of connected broadcasting, TV analytics is a different game. We’re getting data and the subsequent insight quicker than ever before, giving us the chance to use it when it’s most powerful. The industry isn’t stopping there, though. Going forward, I expect to see increases in the availability of real-time data, allowing content owners to see what’s happening with their channels as it’s happening. Tweaks can then be made and problems fixed immediately, with viewers benefiting once again from an improved experience.

This information isn’t just coming directly from the user interfaces either. There’s also a lot to be learned elsewhere on the internet, especially on social media. Today’s young people – the ones driving this connected television revolution – crave interactivity. Platforms like Facebook and Twitter give them an instant, free outlet through which to voice opinions and gripes. It also provides a great opportunity for content owners to learn more about their audiences in general; they can start to understand the types of content certain viewers are most likely to respond to, for example. This applies to advertising as well as actual programming.

Moving on

You’d be forgiven for assuming this new, ultra-efficient way of broadcasting is reserved for those at the top of the industry, but you’d be wrong. The internet’s part in this evolution, most notably the virtualisation of broadcast operations, ensures the changes apply to all. Content owners are no longer forced to invest heavily in infrastructure before they can compete, and can instead work on a more operational basis – they pay for what they use. Data has a massive role to play in this; it’s helping broadcasters make more informed decisions. Then, as we see the speed at which it arrives increase in the coming months and years, things will work even more responsively.

For viewers, the results will be better quality programming, increased convenience, more relevant advertising and an overall enhanced viewing experience. As this happens, consumption and revenue will grow. Everybody wins.

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