Description
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
What you will learn
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.
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.
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.
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.
