À propos de ce cours : Marketers must make the best decisions based on the information presented to them. Rarely will they have all the information necessary to predict what consumers will do with complete certainty. By incorporating uncertainty into the decisions that they make, they can anticipate a wide range of possible outcomes and recognize the extent of uncertainty on the decisions that they make. In Incorporating Uncertainty into Marketing Decisions, learners will become familiar with different methods to recognize sources of uncertainty that may affect the marketing decisions they ultimately make. We eschew specialized software and provide learners with the foundational knowledge they need to develop sophisticated marketing models in a basic spreadsheet environment. Topics include the development and application of Monte Carlo simulations, and the use of probability distributions to characterize uncertainty.
Les destinataires de ce cours : Prerequisites: It is recommended that you complete the "Meaningful Marketing Insights" course offered by Coursera before starting this course. Learners should have the ability to extract information from the data available and make meaningful insights, understanding of regression methods, and basic knowledge of Microsoft Excel.
Créé par : Université Emory
Enseigné par : David Schweidel, Associate Professor of Marketing
Goizueta Business School
| Informations de base | Cours 2 de 6 dans Foundations of Marketing Analytics Specialization |
| Niveau | Intermediate |
| Langue | English |
| Comment réussir | Réussissez tous les devoirs notés pour terminer le cours. |
| Notes des utilisateurs |
Programme de cours
SEMAINE 1
Randomness and Probability
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
3 vidéos, 2 lectures
- Vidéo: Randomness & Probability: An Introduction
- Vidéo: Applications of Randomness & Probability
- Vidéo: Assessing the Value of Information
- 阅读: How Customer Analytics is Speeding the Cure for Parkinson's
- 阅读: Data Driven Donor Management
Noté: Module 1
SEMAINE 2
Conducting Monte Carlo Simulations in Excel
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.
1 vidéo, 4 lectures
- Vidéo: Randomness & Probability Excel Demonstration
- 阅读: Inventory Exercise for Excel Demonstration
- 阅读: Explained: Monte Carlo Simulation
- 阅读: How Our 2016 MLB Predictions Work
- 阅读: The Advantages of Monte Carlo Simulations
Noté: Build-A-Game Assignment
SEMAINE 3
Using Probability Distributions to Model Uncertainty
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.
5 vidéos, 1 lecture
- Vidéo: A General Decision Making Framework
- Vidéo: Properties of Random Variables
- Vidéo: Steps in Using Probability Functions
- Vidéo: Normal Distribution & Other Probability Models
- Vidéo: Warnings in Modeling Uncertainty
- 阅读: Employee Yield Worksheet
Noté: Module 3
SEMAINE 4
Application: Designing Extended Service Warranty Plans
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.
4 vidéos, 4 lectures
- Vidéo: Product Protection Plans
- Vidéo: Company Constraints & Decisions
- Vidéo: Questions to Investigate
- 阅读: Should You Get An Extended Warranty?
- 阅读: Don't Buy Extended Warranties
- Vidéo: Extended Service Warranty Excel Exercise
- 阅读: Designing Extended Warranty Plans - Instructions & Excel Spreadsheet
- 阅读: Poisson Distribution Excel Sheet
Noté: Service Warranty Plans Peer Review
FAQ
Comment cela fonctionne
课程作业
每门课程都像是一本互动的教科书，具有预先录制的视频、测验和项目。
来自同学的帮助
与其他成千上万的学生相联系，对想法进行辩论，讨论课程材料，并寻求帮助来掌握概念。
证书
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Créateurs
Université Emory
Emory University, located in Atlanta, Georgia, is one of the world's leading research universities. Its mission is to create, preserve, teach and apply knowledge in the service of humanity.
Tarification
| Acheter le cours | |
|---|---|
| Accéder au contenu du cours | Disponible |
| Accéder au contenu noté | Disponible |
| Recevoir une Note Finale | Disponible |
| Obtenir un Certificat de Cours partageable | Disponible |
Notation et examens
In one word: USEFUL. And that is a lot these days. I use the concepts (and excel tools) everyday!
Great course with very applicable skills for professional or personal life.
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Just as other courses in the series, this course offers hands-on experience with statistical analysis and many opportunities to apply acquired learnings in practice.