Media & EntertainmentPredictive Analytics

Seven West Media fuels audience growth and ad revenue with an AI Factory built on Databricks

Seven West Media· AustraliaDatabricks Data + AI Platform · Unity Catalog · AI/BI Genie +6

Australian media company Seven West Media built an enterprise-wide 'AI Factory' on Databricks with AI/BI Genie, MLflow and Unity Catalog for predictive audience analytics and re-engagement campaigns, growing daily active users on 7plus by 40%, generating $16 million in incremental ad revenue from lapsed-user re-engagement, and cutting cost per click by 50%.

Overview

Australian media company Seven West Media built an enterprise-wide 'AI Factory' on Databricks with AI/BI Genie, MLflow and Unity Catalog for predictive audience analytics and re-engagement campaigns, growing daily active users on 7plus by 40%, generating $16 million in incremental ad revenue from lapsed-user re-engagement, and cutting cost per click by 50%.

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The challenge

Legacy systems made it difficult for Seven West Media to access real-time insights across billions of events and attributes from its digital and streaming platforms, slowing down decision-making and leaving revenue opportunities on the table.

The solution

Seven built a company-wide 'AI Factory' on the Databricks Data + AI Platform unifying data, models, governance and business applications, using AI/BI Genie for a self-service natural-language chatbot, MLflow to manage the ML model lifecycle, Unity Catalog for governance, and Model Serving, AI Search and Agent Framework with a Databricks Apps front end for a piloted RAG promo-script-generation tool, developed with Databricks Professional Services and Mantel Group.

Predictive AnalyticsConversational AIGenerative AIAgentic AI

Reported business value

The AI Factory grew daily active users 40%, delivered $16 million in incremental ad revenue from re-engaging lapsed users, cut cost per click 50% while raising click-through rates 40%, and let the Genie chatbot answer 400 unique business questions in 30 days, reducing the data team's inbox load by 35%.

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