How Viacom uses Big Data Analytics for improving video experience, audience size & ad revenue

Viacom is one of the largest media companies in the world, delivering more than 170 cable, broadcast and online networks in around 160 countries. Viacom's portfolio includes some household brands such as Comedy Central, Nickelodeon and MTV. Monitoring of the digital networks which are used to pump their content into millions of homes gives them access to a huge amount of data, on how both their systems and their audiences behave. Here is an awesome video representing the Viacom's love for Big Data!

Viacom's Big Data Analytics use cases

  • Improving video experience of its viewers: Delivery of video is at the core of Viacom's business. Particularly with younger audiences, that split second could be the difference between retaining the user and losing them. So, that is a huge area of focus and data is an instrumental part for optimizing the video experience. There are a lot of variables variables at play with the delivery of videos. Internal systems like content delivery systems and ad severs interact with environmental factors like wi-fi connectivity. While there is no real control over these external factors, monitoring these factors leads to insights which could be used to predict when problems will emerge. Viacom has built a real-time analytics platform based around Apache Spark and Databricks, which constantly monitors the quality of video feeds and reallocates resources in real-time when it thinks it will be needed. The key objectives they use the raw data for are 1) Surface trends 2) Isolate areas of opportunity to present a superior viewing experience. Two key metrics that are closely monitored for this are: 1 ) "time to first frame" which indicates how long it takes a video to start 2) "rebuffering rate" which indicates how often the video stutters. These have been shown by the analytics to be primary indicators of whether an audience will settle in to watch a video, or search for something else instead. Thanks to improvements driven by their analytics, Viacom has reduced the time-to-first-frame their viewers experience to around one third of what it was, across their network.
  • Growing the audience: Facebook's “north star” metric (the insight that could guide them to their goal) is to get new users to seven friends within ten days, at which point they are hooked. Same way, Viacom has deduced through analytics, that it needs to get viewers hooked on at least two individual shows. This is because if they can get you to watch two shows you're 350% more likely to stay with us. If we can get you to watch four shows, that goes up to 700% - seven times more likely. This meant that the focus could be switched to getting customers who already regularly enjoy one show to trying out one or two more, to vastly increase their probability of becoming loyal Viacom viewers. The initiative has been "highly successful" for Viacom's business. Some other decisions that could be taken to grow the audience are changes to scheduling, casting, or other factors which will attract viewers. The power of Big Data is that it allows organizations to highlight precisely which of these seemingly "common sense" decisions they should spend time and money implementing.
  • Targeted advertising: TV advertising sales have been consistently falling in recent years as advertisers increase their spending on new media. In reaction to this, Viacom earlier this year announced a partnership with comScore which will allow it to use the ratings organization’s data for its targeted advertising systems. Accurately assessing viewing figures has become a very complicated job in the online age, as audiences spread their viewing across multiple devices, some of which are watched in a group, and some watched in solitary. No "one size fits all" solution has yet been developed, but by collecting data from more sources, more accurate models of viewership can be built, to attract advertisers to Viacom’s channels.