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Marketing Analytics Using Data Science and AI digital marketing analytics in theory



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

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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

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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1 thought on “Marketing Analytics Using Data Science and AI digital marketing analytics in theory”

  1. Please make a tutorial on "How to build a Digital Analytics (through Google Analytics Data) Data Science Product and making a machine learning app in python for deployment and wanted to show a management 10% sales increase and make a decision". Thank you

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