This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.
伊利诺伊大学香槟分校
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週
1完成時間為 6 小時
Course Introduction
With the first module, we will measure and identify satisfied customers to adjust product or service accordingly. To measure the customer satisfaction we will measure expectations, performance and disconfirmation of the offered product or service. We will also provide an overview of marketing analytics used to gauge the effectiveness of different marketing activities. Finally, we will go through measurement and scaling techniques.
20 個視頻 （總計 132 分鐘）, 6 個閱讀材料, 5 個測驗
20 個視頻
Interview with Monica Penagos – MOOC intro8分鐘
Tour of R and RStudio5分鐘
Projects3分鐘
Math Function4分鐘
Scalar Variables6分鐘
Column Vectors9分鐘
Data Frame6分鐘
Data Frame Import2分鐘
Help and Cheat Sheets2分鐘
Interview with Monica Penagos – Intro to Customer Satisfaction1分鐘
Lesson 1-1.1 Introduction to Marketing Analytics and Customer Satisfaction5分鐘
Lesson 1-1.2 Marketing Analtyics – A Brief History12分鐘
Lesson 1-2 Customer Satisfaction12分鐘
Lesson 1-3.1 Measurements and Scaling Techniques – Introduction3分鐘
Lesson 1-3.2 Measurements and Scaling Techniques – Primary Scales of Measurement11分鐘
Lesson 1-3.3 Measurements and Scaling Techniques – Comparative Scaling9分鐘
Lesson 1-3.4 Measurements and Scaling Techniques – Non-Comparative Scaling9分鐘
Lesson 1-4.1 Experiment Design: Key Concepts9分鐘
Lesson 1-4.2 Experiment Design: Controlling for Experimental Errors8分鐘
6 個閱讀材料
Syllabus30分鐘
About the Discussion Forums10分鐘
Glossary10分鐘
Update Your Profile10分鐘
Module 1 Overview20分鐘
Module 1 Readings1 小時 30 分
5 個練習
Orientation Quiz10分鐘
Lesson 1-1 Practice Quiz4分鐘
Lesson 1-2 Practice Quiz4分鐘
Lesson 1-3 Practice Quiz10分鐘
Module 1 Graded Quiz30分鐘
週
2完成時間為 4 小時
Module 2
We will explore the marketing world through process of A/B testing, design of experiments, data analysis, and hypothesis testing. Next, we study Analysis of Variance (ANOVA) which is used to determine significant differences between two or more categorical groups. We will study ANOVA’s assumptions, test inference and different types of ANOVA. We also spend some time in designing experiments.
8 個視頻 （總計 78 分鐘）, 2 個閱讀材料, 4 個測驗
8 個視頻
Lesson 2-1.1 A/B Testing: Introduction11分鐘
Lecture 2-1.2 A/B Testing: Types of Tests7分鐘
Lesson 2-1.3 A/B Testing: R Example10分鐘
Lesson 2-2.1 ANOVA – Introduction14分鐘
Lesson 2-2.2 One-Way ANOVA – Insect Spray Example8分鐘
Lesson 2-2.3 One-Way ANOVA – Insect Spray Example in R10分鐘
Lesson 2-2.4 Two-Way ANOVA – Tooth Growth Example11分鐘
2 個閱讀材料
Module 2 Overview20分鐘
Module 2 Readings7分鐘
3 個練習
Lesson 2-1 Practice Quiz8分鐘
Lesson 2-2 Practice Quiz16分鐘
Module 2 Graded Quiz30分鐘
週
3完成時間為 4 小時
Module 3
We will learn about the Binary Outcome model using Logit function. The Logistic regression is sued when the dependent variable has a binary outcome. Next, we cover Multidimensional Scaling (MDS). MDS is used in marketing to understand the pair-wise similarity of the individual cases of data-set. This technique maps the individual cases onto a 2-dimensional Cartesian graph for visual analysis.
7 個視頻 （總計 63 分鐘）, 2 個閱讀材料, 4 個測驗
7 個視頻
Lesson 3-1.1 Binary Outcome Model – Logit Model12分鐘
Lesson 3-1.2 Binary Outcome Model – Logit Model Example 111分鐘
Lecture 3-1.3 Binary Outcome Model – Logit Model Example 27分鐘
Lesson 3-2.1 Multi-Dimensional Scaling Introduction10分鐘
Lesson 3-2.2 Conducting an MDS Analysis9分鐘
Lesson 3-2.3 Multi-Dimensional Scaling – R Example9分鐘
2 個閱讀材料
Module 3 Overview20分鐘
Module 3 Readings30分鐘
3 個練習
Lesson 3-1 Practice Quiz4分鐘
Lesson 3-2 Practice Quiz5分鐘
Module 3 Graded Quiz30分鐘
週
4完成時間為 4 小時
Module 4
We will learn about Conjoint Analysis to understand how individuals combine and weigh different attributes. We will introduce the concept of conjoint analysis and part-worth utilities. We will survey different approaches before focusing our attention to the classical conjoint analysis. We will reinforce our understanding by studying an example in detail before running examples of the analysis in R
11 個視頻 （總計 70 分鐘）, 2 個閱讀材料, 3 個測驗
11 個視頻
Lecture 4-1.1 Conjoint Analysis – Introduction7分鐘
Lesson 4-1.2 Conjoint Analysis – Data Collection Methods9分鐘
Lesson 4-1.3 Conjoint Analysis – Types of Conjoint Analysis2分鐘
Lesson 4-1.4 Conjoint Analysis – Part-Worth Utilities3分鐘
Lesson 4-1.5 Conjoint Analysis Example – Ferry Fares10分鐘
Lesson 4-1.6 Conjoint Analysis – Attributes10分鐘
Lesson 4-1.7a Conjoint Analysis R Example – Setup5分鐘
Lesson 4-1.7b Conjoint Analysis R Example – Part 110分鐘
Lesson 4-1.7c Conjoint Analysis R Example – Part 25分鐘
Course Summary: Applying Data Analytics in Marketing1分鐘
2 個閱讀材料
Module 4 Overview20分鐘
Module 4 Readings1小時
2 個練習
Lesson 4-1 Practice Quiz24分鐘
Module 4 Graded Quiz30分鐘
4.4
3 個審閱來自Applying Data Analytics in Marketing的熱門評論
it was a perfect course , which gave me the full picture of how to make a marketing testing and evaluation
講師
Sung Won Kim
Associate ProfessorBusiness Administration
立即開始攻讀碩士學位
此 課程 隸屬於 伊利诺伊大学香槟分校 提供的 100% 在線 Master of Business Administration (iMBA)。如果您被錄取參加全部課程，您的課程將計入您的學位學習進程。
關於 伊利诺伊大学香槟分校
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
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