Viacom

Customer Case Study

Viacom, with its 170 cable, broadcast and online networks in around 160 countries, is transforming itself into a data-driven enterprise — collecting and analyzing petabytes of network data to increase viewer loyalty and revenue.

Vertical Use Case

Optimize user experience
Customer retention
Targeted advertising

Technical Use Case

Data Ingest and ETL
Machine Learning
Streaming Analytics

The Challenges

Improving user experience: Streaming petabytes of video data across the world puts a strain on the delivery systems, resulting in videos failing to load or constantly stuttering as they rebuffer.
Growing the audience: Making sense from huge troves of viewing data and determining the best actions to drive viewer retention and loyalty.
Targeted advertising: With TV ad sales falling in recent years, Viacom needed to find better ways to engage with their audience via advertising.

The Solution

Viacom has built a real-time analytics platform based on Apache^® Spark^™ and Databricks, which constantly monitors the quality of video feeds and reallocates resources in real-time when needed. Databricks has helped Viacom:

Predict trends and issues to provide superior viewing experience: Reduced video start delay by 33%.
Increase customer loyalty: Leveraged data to identify how to increase customer retention by 3.5-7x.
Improve ad conversions: Targeted customers with personalized ads based on comScore ratings and viewing behavior.

Databricks lets us focus on business problems and makes certain processes very simple. Now it’s a question of how do we bring these benefits to others in the organization who might not be aware of what they can do with this type of platform.

Dan Morris
 Senior Director of Product Analytics , Viacom

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