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).
Meaningful Marketing Insights
This course is part of Foundations of Marketing Analytics Specialization
Instructor: David Schweidel
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There are 5 modules in this course
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
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
5 videos3 readings1 assignment1 discussion prompt
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
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.
What's included
2 videos3 readings1 assignment1 peer review1 discussion prompt
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Emory University
University of Virginia
University of Pennsylvania
University of Maryland, College Park
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Reviewed on Nov 11, 2017
The last 2 video lectures: Customer Valuation Excel Demonstration and Inventory Management Excel Demonstrationm were very well explained and taught me something new and useful.
Reviewed on Nov 16, 2023
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Reviewed on May 8, 2017
Very interesting course with lots of career pertinent information and learning.
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