Meaningful Marketing Insights

Meaningful Marketing Insights

This course is part of Foundations of Marketing Analytics Specialization

Instructor: David Schweidel

Access provided by Interbank

37,651 already enrolled

5 modules

Gain insight into a topic and learn the fundamentals.

291 reviews

Intermediate level

Some related experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

90%

Most learners liked this course

5 modules

Gain insight into a topic and learn the fundamentals.

291 reviews

Intermediate level

Some related experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

90%

Most learners liked this course

Skills you'll gain

Tools you'll learn

Microsoft Excel

Details to know

Shareable certificate

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Assessments

4 assignments¹

AI Graded see disclaimer

Taught in English

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This course is part of the Foundations of Marketing Analytics Specialization

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There are 5 modules in 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).

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

What's included

1 video2 readings1 discussion prompt

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.

What's included

4 videos3 readings1 assignment1 discussion prompt

4 videos Total 43 minutes

Course Objectives & Example 1: Political Advertising Expenditures 12 minutes
Course Goals & Example 2: Performing Arts Centers 9 minutes
Organizing Data 11 minutes
The Motion Picture Industry 12 minutes

3 readings Total 30 minutes

How Companies Learn Your Secrets 10 minutes
Big Data in the Big Apple 10 minutes
Motion Picture Industry Example Data Set 10 minutes

1 assignment Total 25 minutes

Module 2 Quiz 25 minutes

1 discussion prompt Total 15 minutes

Categorical Variables in the Motion Picture Industry 15 minutes

What's included

5 videos3 readings1 assignment1 discussion prompt

5 videos Total 48 minutes

Excel Analysis of Motion Picture Industry Data 13 minutes
Displaying Conditional Distributions 5 minutes
Analyzing Qualitative Variables 4 minutes
Steps in Constructing Histograms 11 minutes
Common Descriptive Statistics for Quantitative Data 15 minutes

3 readings Total 40 minutes

Giving Viewers What They Want 10 minutes
Why Personalization is Key for Content Marketing 5 minutes
Assignment: Survey Analysis Assignment 25 minutes

1 assignment Total 30 minutes

Module 3 Quiz 30 minutes

1 discussion prompt Total 15 minutes

Visualizing Data: Technique Review 15 minutes

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.

What's included

4 videos2 readings1 assignment1 discussion prompt

4 videos Total 41 minutes

Regression-Based Modeling 10 minutes
Introduction to Customer Analytics 10 minutes
Customer Choices Drive Business Decisions 9 minutes
Illustrating Customer Analytics in Excel 11 minutes

2 readings Total 45 minutes

How to Find Your Most Valuable Customers 20 minutes
Assignment: Customer Acquisition Example 25 minutes

1 assignment Total 25 minutes

Module 4 Quiz 25 minutes

1 discussion prompt Total 15 minutes

Logit v. Probit Models 15 minutes

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.