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Course Description

In this course, you will explore the growth and impact of increasing international and domestic (U.S.) investment in digital advertising. In detailing the two main approaches — display and sponsored search advertising — you’ll understand how most "free" media markets are actually “two-sided” markets, requiring platforms to satisfy two user groups in order to make a profit. You will become familiar with the critical metrics used to evaluate ad performance as you go hands-on to compute the ROI of various activities based on data provided within a scenario. From here, you will examine the need for multi-touch attribution and become aware of the intricacies of rules-based and data-based attribution. Finally, you will learn about randomized field experiments as a method for evaluating ad performance, as well as the pros and cons inherent in this approach.

You are required to have completed the following course or have equivalent experience before taking this course:

  • Exploring Data Sets With R

Faculty Author

Sachin Gupta

Benefits to the Learner

  • Compute metrics to evaluate the effectiveness of sponsored search advertising
  • Compute the return of ad dollars spent as a key bottom-line metric
  • Use rules-based attribution and data-based attribution to give credit to individual digital touch points using customer path data
  • Design and use randomized field experiments to measure advertising performance

Target Audience

  • Marketing professionals
  • Business analysts
  • Managers using data insights to make business decisions
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Cornell Johnson Graduate School of Management
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