Ce cours fait partie de la Spécialisation Foundations of Marketing Analytics
Marketing Analytics Capstone Project
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À propos de ce cours
3.7
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This capstone project will give you an opportunity to apply what we have covered in the Foundations of Marketing Analytics specialization. By the end of this capstone project, you will have conducted exploratory data analysis, examined pairwise relationships among different variables, and developed and tested a predictive model to solve a marketing analytics problem. It is highly recommended that you complete all courses within the Foundations of Marketing Analytics specialization before starting the capstone course.
Programme du cours : ce que vous apprendrez dans ce cours
Week
1Marketing Analytics Project Description
This module will define the goals and activities for the marketing analytics capstone project.
2 lectures
2 lectures
Capstone Overview15 min
Pre-Readings30 min
Week
2Exploratory Analysis
In this module, we will begin to examine individual variables and their relationship to the status of the loan. Note, this module includes review items from previous courses in the specialization. This content is not required, but recommended as content to revisit.
9 vidéos (Total 91 min), 2 lectures, 1 quiz
9 vidéos
Meaningful Marketing Insights - Course Goals & Example 2: Performing Arts Centers8 min
Meaningful Marketing Insights - Organizing Data10 min
Meaningful Marketing Insights - The Motion Picture Industry12 min
Meaningful Markting Insights - Excel Analysis of Motion Picture Industry Data13 min
Meaningful Marketing Insights - Displaying Conditional Distributions4 min
Meaningful Marketing Insights - Analyzing Qualitative Variables3 min
Meaningful Marketing Insights - Steps in Constructing Histograms11 min
Meaningful Marketing Insights - Common Descriptive Statistics for Quantitative Data14 min
2 lectures
Activity & Explanation of Review Content45 min
Meaningful Marketing Insights - Parts 2 - 340 min
Week
3Data Preparation and Model Building
While there are many ways to build a classification model, we will focus on using logistic regression, a common tool for marketing problems in which the dependent variable is binary. We will begin by choosing a single predictor variable and then determine which other variables need to be added to our analysis. In this module, we will focus on developing alternative models that all have a single predictor.
3 lectures, 1 quiz
3 lectures
Data Preparation Instructions20 min
Populating the Template20 min
Review Forecasting Models for Marketing Decisions, Parts 1 - 310 min
1 exercice pour s'entraîner
Logistic Regression Practice6 min
Week
4Model Validation and Comparison
In the previous module, we estimated a model linking home ownership to whether or not a loan is considered risky. In this module, we will begin by assessing the accuracy of this model relative to a naïve model. We will then use this spreadsheet as a means of assessing how well the model performs when different predictors are used.
1 lecture, 2 quiz
1 lecture
Model Validation20 min
1 exercice pour s'entraîner
Model Validation5 min
Enseignant
David Schweidel
Associate Professor of MarketingGoizueta Business School
À propos de 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.
À propos de la Spécialisation Foundations of Marketing Analytics
In this specialization you will learn how to:
• Find, extract, organize and describe data to support business decisions
• Identify, quantify and interpret relationships between variables
• Derive customer insights from your data
• Develop spreadsheet models to analyze data, evaluate risk and optimize business decisions
• Present and justify a course of action to management
The capstone project will give you an opportunity to apply what has been covered in the specialization to solve a marketing analytics problem.
Foire Aux Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
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