Course Summary
Learn how to apply data analytics to drive decision-making in marketing. This course covers topics such as customer segmentation, predictive modeling, and digital marketing analytics.Key Learning Points
- Understand how data analytics can be used to inform marketing decisions
- Learn about different types of data and how to analyze them
- Gain hands-on experience with data analytics tools such as Python and R
Related Topics for further study
Learning Outcomes
- Apply data analytics techniques to real-world marketing problems
- Understand how to use data to improve customer segmentation and targeting
- Develop predictive models to inform marketing decision-making
Prerequisites or good to have knowledge before taking this course
- Basic understanding of statistics
- Familiarity with programming languages such as Python or R
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video Lectures
- Hands-on Projects
Similar Courses
- Marketing Analytics
- Digital Marketing
- Marketing Mix Implementation
Related Education Paths
Related Books
Description
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.
Outline
- Course Introduction
- Coursera Course Introduction ***
- Instructor Bio: Joseph Yun ***
- Interview with Monica Penagos – MOOC intro
- Learn on Your Terms
- Module 1 Overview ***
- Interview with Monica Penagos – Intro to Customer Satisfaction
- Lesson 1-1.1 Introduction to Marketing Analytics and Customer Satisfaction
- Lesson 1-2.1 Customer Satisfaction
- Lesson 1-3.1 Measurements and Scaling Techniques – Introduction
- Lesson 1-3.2 Measurements and Scaling Techniques – Primary Scales of Measurement
- Lesson 1-3.3 Measurement and Scaling Techniques – Comparative Scaling ***
- Lesson 1-3.4 Measurements and Scaling Techniques – Non-Comparative Scaling
- Lesson 1-4.1 Experiment Design: Key Concepts
- Lesson 1-4.2 Experiment Design: Controlling for Experimental Errors
- Syllabus
- About the Discussion Forums
- Glossary
- Learn More About Flexible Learning Paths
- Module 1 Overview
- Module 1 Readings & Files
- Orientation Quiz
- Lesson 1-1 Practice Quiz
- Lesson 1-2 Practice Quiz
- Lesson 1-3 Practice Quiz
- Module 1 Graded Quiz
- Module 2
- Module 2 Overview ***
- Interview with Monica Penagos – A/B Testing and ANOVA in Practice
- Lesson 2-1.1 A/B Testing: Introduction
- Lecture 2-1.2 A/B Testing: Types of Tests
- Lesson 2-1.3 A/B Testing: R Example
- Lesson 2-2.1 ANOVA – Introduction
- Lesson 2-2.2 One-Way ANOVA – Insect Spray Example
- Lesson 2-2.3 One-Way ANOVA – Insect Spray Example in R
- Lesson 2-2.4 Two-Way ANOVA – Tooth Growth Example
- Module 2 Overview
- Module 2 Readings & Files
- Lesson 2-1 Practice Quiz
- Lesson 2-2 Practice Quiz
- Module 2 Graded Quiz
- Module 3
- Module 3 Overview ***
- Interview with Monica Penagos – Choice Models in Practice
- Lesson 3-1.1 Binary Outcome Model – Logit Model
- Lesson 3-1.2 Binary Outcome Model – Logit Model Example 1
- Lesson 3-1.3 Binary Outcome Model – Logit Model Example 2
- Lesson 3-1.4 Introduction to Forecasting: Linear Regression
- Module 3 Overview
- Module 3 Readings & Files
- Lesson 3-1 Practice Quiz
- Module 3 Graded Quiz
- Module 4
- Module 4 Overview
- Lesson 4-1.1 Introduction to Text Summarization
- Lesson 4-1.2 Introduction to the Social Media Macroscope (SMM)
- Lesson 4-1.3 N-gram Frequency Count and Phrase Mining
- Lesson 4-2.1 LDA Topic Modeling
- Lesson 4-2.2 Machine-Learned Classification and Semantic Topic Tagging
- Course Summary: Applying Data Analytics in Marketing
- Gies Online Programs
- Module 4 Overview
- Module 4 Readings & Files
- Congratulations!
- Get Your Course Certificate
- Lesson 4-1 Practice Quiz
- Lesson 4-2 Practice Quiz
- Module 4 Graded Quiz
Summary of User Reviews
Discover how to apply data analytics in marketing with this Coursera course. Users have rated this course highly for its comprehensive content and practical approach. Many users found the hands-on exercises and real-world examples to be particularly helpful.Key Aspect Users Liked About This Course
The hands-on exercises and real-world examples provided in this coursePros from User Reviews
- Comprehensive content that covers a range of topics
- Practical approach with real-world examples
- Hands-on exercises that help reinforce learning
- Engaging and knowledgeable instructors
- Flexible schedule and self-paced learning
Cons from User Reviews
- Some users found the course to be too basic
- Limited interaction with instructors and peers
- Not suitable for advanced learners
- Some technical issues with the platform
- No certification or accreditation provided
Joseph T. Yun
4.4 Raiting
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