Big data & TV
By Ben Dugdale
30th March 2017

I’m the first to admit I love the occasional TV binge-watch; I love following TV shows and finding new ones. Any of us that subscribe to streaming services like Netflix or Amazon Prime get used to recommendations made and we know they are tailored to meet us. I want to have a look at the data behind this and how it not just predicts shows for us to watch but how is also dictates what shows the companies make, and how they make updates to the services.

Making Updates

All apps make updates, whether the user likes it or not but some companies like Netflix are using their customer data to help them decide what to push out or not.

Netflix has a lot of data to deal with, in a recent conference it was stated that ‘they have over 86 million members globally, streaming over 125 million hours of content per day. This results in a data warehouse which is over 60 petabytes in size’. That is a lot of big data for Netflix to analyse and find patterns and trends from, one thing they do in order to spot these patterns is to do a/b tests on a select user group and analyse how they interact with the changes. This can then help to decide on the final outcome for the majority of their users.

Making Shows

Typically before streaming services had access to all this data TV companies had to rely on ratings to know what shows the audience want to watch, but in this online, digital world big data is now helping to play a part.

By looking at their customer’s data and their viewing habits the streaming services know what will be a hit, and what to put their money in to. The services can analyse what you view, when you view it, if you pause, rewind, fast-forward or anything else you do on the service. By analysing this data the company know what shows each demographic will react positively to and they can market and recommend them accordingly, almost making sure it is a hit with the right viewers.  

And this data is not just dictating which shows the services should be making, it can tell them what shows they should be buying. While services like Amazon are making original series, like The Man in the High Castle, it is also buying in to series made by other companies. By looking at their audiences viewing habits they know what shows will work best, for example in 2014 Amazon made a deal with HBO, who create shows like Silicon Valley, by analysing the user behaviour Amazon knew their audience typically react positively to this content.

We’re now in a world where TV we like is right in front of us, we no longer have to scroll though the TV guide for endless hours looking for something to take our fancy, the services we subscribe to are putting them in front of us as soon as we turn on. The data collected is only to grow and with that, hopefully, more high quality good TV!

Do you like how streaming services are using your data to make predictions? I’d love to hear your thoughts in the comments below.

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This blog was originally published on LinkedIn. To read the original article click here

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