In this course, learners will be able to describe what digital analytics actually means, and how companies should think about the capabilities they want to build when it comes to digital analytics. Learners will engage in several aspects of data and analytics including machine learning, collecting data through tagging, cookies and dashboards, and understanding performance.

Objectives

  • Describe what digital analytics actually means, and how companies should think about the capabilities they want to build when it comes to digital analytics.
  • Identify the different types of data, especially “batch” vs. “streaming”.
  • Demonstrate how to extend the practice of testing & experimentation into a program of optimization
  • Demonstrate the basic application of machine learning to content optimization
  • Recognize the value of and process for collecting data through “tagging”, including collecting web data, and link tagging for email and paid media.
  • Differentiate between first party and third party cookies.
  • Examine the performance and context data available through owned media dashboards for Web and Email analytics
  • Demonstrate how to link marketing KPIs to business performance KPIs
  • Recognize how channels work together across the consumer journey
  • Demonstrate how to use the omni-channel, cross-journey linkage to performance to plan the most efficient and effective investments in marketing

About this Class

58:45

Minutes of education

8

Video Lessons

Instructor

Scot Wheeler's picture

Scot Wheeler

Scot Wheeler is the Director of Marketing Analytics and Consumer Insights at the online grocer Peapod. Scot is also an adjunct lecturer in Integrated Marketing Communications at Northwestern University, where he teaches Digital Analytics. He is a leader in digital analytics delivery, with over a decade of exper more.

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