Emory University
Managing Uncertainty in Marketing Analytics
Emory University

Managing Uncertainty in Marketing Analytics

This course is part of Foundations of Marketing Analytics Specialization

Taught in English

Some content may not be translated

David Schweidel

Instructor: David Schweidel

11,117 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.3

(68 reviews)

Intermediate level
Some related experience required
10 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

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Assessments

2 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.3

(68 reviews)

Intermediate level
Some related experience required
10 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Foundations of Marketing Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

Module 1 focuses on developing an understanding where randomness appears in marketing problems. You will learn basic rules for calculating the probability of outcomes. We will also examine how these rules can be applied to determine the value of information

What's included

3 videos2 readings1 quiz

Building on the basics of randomness and probability discussed in Module 1, we examine the use of Monte Carlo simulations for incorporating randomness into business problems. Using Microsoft Excel, we will build a tool that conducts a Monte Carlo simulation. We will use this tool to evaluate the best course of action for a particular business problem.

What's included

1 video4 readings1 peer review

In Module 3, we look at the use of probability distributions as a means of characterizing uncertainty. We initially look at how uncertainty is incorporated into a general decision making framework. We then turn our attention to different probability distributions that can be used to model uncertainty, depending on the nature of the data. We examine the application of these probability distributions to assess the likelihood of events using features within Microsoft Excel.

What's included

5 videos1 reading1 quiz

Building the the discussion of probability distributions in Module 3, we apply this knowledge to a specific application: the design of extended service warranty plans. We provide an overview of the business problem and discuss how to incorporate uncertainty in customers' use of the warranty plan using the Poisson distribution. Using Microsoft Excel, we design a spreadsheet tool that enables a user to adjust features of the service plans. By comparing firm profit under different scenarios, we investigate how different features of the service plan result in risk being shared by the consumer and the firm.

What's included

4 videos4 readings1 peer review

Instructor

David Schweidel
Emory University
6 Courses62,123 learners

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4.3

68 reviews

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