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.
Industry
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.