Data analytics is heavily impacting the way we consume TV content. We can see this presently in how TV providers are trying to connect to viewers through the Internet.
The central force driving this change is on-demand entertainment mainly based on viewers’ behavior.
In an excerpt from a Royal Television Society’s event, Mark Connolly said: “There is no doubt that TV viewing is having to change because of Netflix and Amazon Prime.”
TV had to change in some ways that were necessary so that people will not dump it for Internet content or have to frequently switch from one channel to another.
Most of the changes are direct results of data analytics in Singapore and you can see how below.
1) More Investment in Big Data: TV Channels had to up their Data Analytics Game
Some form of data analytics was not absent on TV but it seems Internet giants have used the same content and have applied deep learning in ways that was not applied in the TV business.
The Broadcasting Audience Research Board, (BARB) has provided official data about TV viewers since 1981 and they are on course to invest millions of pounds to get similar results that the data analytics tools give tech giants like Netflix.
Individual TV channels are not resting on their laurels too. For those who can make use of BARB, it will cost them money to buy into, and they invest within their company too. For example, CNN had invested $20million about 4 years ago, presently they are building on that data analytics investment.
2) Discovery into who is watching what and if content will sell
If you can predict what the audience will like more accurately, you will have higher TV viewership, more money from advertisement, and higher ratings. This is what Netflix does very well because they know how to use the ‘big data’ and now traditional TV is laying their hands BI technology.
A good example of Data Analytics applied in TV is the success of AMC’s TV shows which was largely due to IBM’s Business Intelligence tool. This ability to know what is hot in demand has made TV pause and play – and downloadable content from TV to become relevant.
3) Showing Targeted Adverts to Viewers (AdSmart)
Sky TV had launched AdSmart since 2014 and this allows advertisers to target advertisements to households. The data analytics powered solution saw TV channel switching drop by 33% and it’s given advertisers more control over ads placement. This development and other BI involvement in TV has played its part in the growth in TV advertising in the last 5 years.
4) Using Social Media Analytics to decide what goes live
Data Analytics is Helping TV Channels to determine what contents to promote
Social media indicators are so important for TV nowadays. Advertisers look at these numbers and the TV networks have to get their numbers up. So it makes sense that TV networks are promoting their channels on TV networks and social media. They are using BI tools to determine which content to promote and why.
5) More Personalized Regional Broadcasting
Well, this is not entirely new, but it makes sense from a data analytic standpoint that regional broadcasts need to be divided into finer audience segments.
We saw what AdSmart offers and you cannot just ignore the temptation to predict a likely future where CNN, for example, will have TV programming for each street in a city.
Certainly, with the possibility of faster data transfer, TV networks will be able to access real-time data from multiple channels faster and do so simultaneously.
Ultimately, this data-driven change will further blur the line between mainstream TV and Internet entertainment.