Subscriber Analytics and the Snowflake Media Data Cloud in action

There’s been a lot of excitement about Snowflake‘s new Media Data Cloud and its potential to transform the way companies in the media and entertainment industry store and use data. But how does it work in practice? 

Using subscriber analytics as an example, we can see how Snowflake’s Media Data Cloud enables intelligent, data-driven decision making. Leveraging the Media Data Cloud, an organization focused on improving customer lifetime value, or the total revenue associated with a customer from acquisition to churn, is able to:

• Understand and quantify all subscribers and their value to the organization
• Improve the effectiveness of marketing and acquisition efforts
• Make optimal marketing decisions driven by intelligent machine learning models

The key to effective decision making is removing data silos and seamlessly integrating external data sources via the Snowflake Media Data Cloud. The organization continuously streams first-party data, PII, subscription revenue, and marketing assets into a privacy-compliant secure raw zone hosted in Snowflake. Then the data is automatically and continuously validated and transformed using streams and tasks in the harmonized layer.

Analyzing first party data isn’t enough, though. The organization needs to seamlessly integrate additional external sources (such as identity, demographic, or psychographic data) to improve marketing effectiveness. This is done in the harmonized layer using the Snowflake Media Data Cloud and data sharing. Finally, they can get a unified view of first- and third-party data in the analytics layer, providing the entire organization with a single version of truth that is always up to date. 

Data model and media data cloud

The Media Data Cloud facilitates highly effective data models that integrate external data for identity resolution, enrichment, and analysis. 

Starting with first-party data sets, we can build a logical, well organized model that integrates several domains – subscription, marketing, and viewership data, for example.

But in order to layer in additional data assets from the Media Data Cloud, we take a step to resolve identities natively in Snowflake. For example, Experian has built and deployed a Snowflake-native ID Resolution Solution that operates directly inside a cleanroom environment. The data is stored and analyzed in a controlled environment for a predetermined amount of time, after which the data expires, which ensures improved data security and privacy. Experian is already an industry leader in Identity Resolution, and now with the Media Data Cloud we can capitalize on their high match rates directly using Snowflake.

With an expanded identity graph and common identifier in the Snowflake Media Data Cloud, we can easily access enriched audience and segment data instantly through simple joins from other providers to the relational data model.