Attacking marketing data with machine learning has yielded some powerful outcomes. Until now, the projects have been mostly rear-view-mirror analysis, but new machine learning models support an open-loop live data operating model.
Learn how to use data science and AI for marketing analytics:
– Key data repositories in the marketing stack – where are the data?
– Normalizing the marketing data ETL process, and staying sane
– Moving from manual analytics to live data analysis
– Looking for the low hanging fruit in marketing optimizations
– Building the marketing ROMI real-time dashboard
– Building feedback loops for “lights out” optimization
– Maintain a working “Notebook-Based” approach through the lifecycle
Speakers:
Grover Righter, Chief Data Scientists at Zepl
Ganesh Subramanian, Director of Product Marketing at Snowflake
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Marketing Analytics Using Data Science and AI
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Marketing Analytics Using Data Science and AI
digital marketing analytics in theory
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