Like Your TV Programming? It’s All About Data Integration

TV Programming Driven by Data Integration
TV Programming Driven by Data Integration
In the past, TV ratings were not delivered quickly: It often took months before networks received ratings books. The data often came as a surprise at that late date, and called into question past programming decisions.

Today, The Netherlands TV industry body, Stichting KijkOnderzoek (SKO), delivers daily Online TV ratings to the market.  Working in partnership with data scientists from Kantar Media, SKO is the first TV network in the world to deliver daily ratings data in granular detail.  While streaming services, such as Netflix and Amazon, have automated consumption and ratings monitoring, network TV had to rely on less sophisticated and slower mechanisms.

The SKO ratings report the online consumption of TV programs, initially from NPO, RTL Netherlands and SBS broadcasting.  Moreover, these extended TV ratings enable advertisers, agencies, and broadcasters to monitor and monetize online reach and viewing behavior across online TV audiences.  In other words, they can determine if the shows are well received by the right audience, including demographics, which allows advertisers to target advertising for the maximum effect.

This is the first phase of SKO’s Video Data Integration Model, which integrates data sources for all online television programming and commercial viewing.  While there have been aspects of data integration ratings for years, this is the first time that networks can see so much, so soon, and react in a timely manner to the data feeds and intelligence it’s able to provide.

Many privacy advocates may push back in this data-driven understanding of our viewing habits.  As someone who watches a lot of TV, I’m happy to share my ratings information so the networks and streaming services can provide better content.  The ads sent my way are okay as well.

Data analytics, and data integration, are becoming the largest driver of emerging networks such as Netflix and Amazon. 

The ability to target content keeps the subscribers happy, and provides a custom and personalized experience for the viewer. For example, my interest in documentaries drives suggestions for other similar documentaries that I can watch on-demand.  This saves me from having to cull through the hundreds of shows to find ones that are similar to my interests.

Data integration is a key technology here, considering that the data must be analyzed pretty much in real time.  Data integration allows me to customize my viewing experience, and make sures that the networks and streaming services understand the value and quality of the programming.

Shows that are rated low, and thus don’t drives the viewers, will be removed.  Shows that are rated high will be picked up for more seasons.  Other shows will be developed by understanding the level of interest in a certain type of show.  For example, the Netflix documentary “Making a Murderer” is hugely popular, and shows it in ratings and streams.  It will undoubtedly spin off similar documentaries, based upon the data that Netflix sees in real-time, and can analyze at any time.

Data is good.  No matter if it’s coming from our set-top-boxes, or tracking a business.  The ability to make use of that data when and where you need it is where the real power lies.