Meaningful Marketing Insights

About this course: With marketers are poised to be the largest users of data within the organization, there is a need to make sense of the variety of consumer data that the organization collects. Surveys, transaction histories and billing records can all provide insight into consumers’ future behavior, provided that they are interpreted correctly. In Introduction to Marketing Analytics, we introduce the tools that learners will need to convert raw data into marketing insights. The included exercises are conducted using Microsoft Excel, ensuring that learners will have the tools they need to extract information from the data available to them. The course provides learners with exposure to essential tools including exploratory data analysis, as well as regression methods that can be used to investigate the impact of marketing activity on aggregate data (e.g., sales) and on individual-level choice data (e.g., brand choices). To successfully complete the assignments in this course, you will require Microsoft Excel. If you do not have Excel, you can download a free 30-day trial here: https://products.office.com/en-us/try

Who is this class for: This course is aimed at those familiar with business and marketing concepts or those currently working in a business analyst or marketing research role.

Created by:  Emory University

• Taught by:  David Schweidel, Associate Professor of Marketing

  Goizueta Business School

Basic Info Course 1 of 6 in the Foundations of Marketing Analytics Specialization Level Intermediate Commitment 5 weeks of study, 2-3 hours/week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.3 stars Average User Rating 4.3See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Emory University 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.

Syllabus


WEEK 1


Meet Dr. Schweidel & Course Overview
In this module, students will be introduced to the instructor, Dr. David Schweidel and get and overview of the course.


1 video, 2 readings expand

1. Video: Meet Dr. Schweidel
2. Reading: Getting Started
3. Reading: A Note About Exercises & Quizzes
4. Discussion Prompt: Introduce Yourself

WEEK 2


Exploring your Data with Visualization and Descriptive Statistics, Part 1



Modules 2 and 3 focus on identifying appropriate descriptive statistics (measures of central tendency and dispersion) for different types of data, as well as recoding data using reference commands to prepare it for analysis. Additionally, you will manipulate and summarize data using pivot tables in Excel, produce visualizations that are appropriate based on the type of data being analyzed, and interpret statistics and visualizations to draw conclusions to address relevant marketing questions.


4 videos, 3 readings expand

1. Video: Course Objectives & Example 1: Political Advertising Expenditures
2. Video: Course Goals & Example 2: Performing Arts Centers
3. Video: Organizing Data
4. Video: The Motion Picture Industry
5. Reading: How Companies Learn Your Secrets
6. Reading: Big Data in the Big Apple
7. Discussion Prompt: Categorical Variables in the Motion Picture Industry
8. Reading: Motion Picture Industry Example Data Set

Graded: Module 2 Quiz

WEEK 3


Exploring your Data with Visualization and Descriptive Statistics, Part 2



Modules 2 and 3 focus on identifying appropriate descriptive statistics (measures of central tendency and dispersion) for different types of data, as well as recoding data using reference commands to prepare it for analysis. Additionally, you will manipulate and summarize data using pivot tables in Excel, produce visualizations that are appropriate based on the type of data being analyzed, and interpret statistics and visualizations to draw conclusions to address relevant marketing questions.


5 videos, 3 readings expand

1. Video: Excel Analysis of Motion Picture Industry Data
2. Video: Displaying Conditional Distributions
3. Video: Analyzing Qualitative Variables
4. Video: Steps in Constructing Histograms
5. Video: Common Descriptive Statistics for Quantitative Data
6. Reading: Giving Viewers What They Want
7. Reading: Why Personalization is Key for Content Marketing
8. Reading: Assignment: Survey Analysis Assignment
9. Discussion Prompt: Visualizing Data: Technique Review

Graded: Module 3 Quiz

WEEK 4


Regression Analysis for Marketing Data



In this module, you will be asked to determine the appropriate type of regression for different types of marketing data and will perform regression analysis to assess the impact of marketing actions on outcomes of interest, such as sales, traffic, and brand choices. You will also be asked to interpret regression output to understand overall model performance and importance of different predictors, as well as make predictions using the appropriate regression model.


4 videos, 2 readings expand

1. Video: Regression-Based Modeling
2. Video: Introduction to Customer Analytics
3. Video: Customer Choices Drive Business Decisions
4. Video: Illustrating Customer Analytics in Excel
5. Reading: How to Find Your Most Valuable Customers
6. Reading: Assignment: Customer Acquisition Example
7. Discussion Prompt: Logit v. Probit Models

Graded: Module 4 Quiz

WEEK 5


From Analysis to Action



This final module will connect the results of regression analysis to marketing decisions. You will learn to build tools that allow users to evaluate outcomes based on different marketing decisions, as well as characterize the extent of uncertainty in outcomes based on the selected marketing decisions.


2 videos, 3 readings expand

1. Video: Customer Valuation Excel Demonstration
2. Video: Inventory Management Excel Demonstration
3. Reading: Encouraging TV Binge Watching May Backfire On Advertisers
4. Reading: Use Big Data to Create Value for Customers, Not Just Target Them
5. Reading: Assignment: Using Regression for Inventory Management
6. Discussion Prompt: Course Reflection

Graded: Module 5 Quiz
Graded: Acquisition & Retention Assignment