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.
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주
1완료하는 데 1시간 필요
Marketing Analytics Project Description
This module will define the goals and activities for the marketing analytics capstone project.
2 readings
2개의 읽기 자료
Capstone Overview15m
Pre-Readings30m
주
2완료하는 데 4시간 필요
Exploratory 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 videos (Total 91 min), 2 readings, 1 quiz
9개의 동영상
Meaningful Marketing Insights - Course Goals & Example 2: Performing Arts Centers8m
Meaningful Marketing Insights - Organizing Data10m
Meaningful Marketing Insights - The Motion Picture Industry12m
Meaningful Markting Insights - Excel Analysis of Motion Picture Industry Data13m
Meaningful Marketing Insights - Displaying Conditional Distributions4m
Meaningful Marketing Insights - Analyzing Qualitative Variables3m
Meaningful Marketing Insights - Steps in Constructing Histograms11m
Meaningful Marketing Insights - Common Descriptive Statistics for Quantitative Data14m
2개의 읽기 자료
Activity & Explanation of Review Content45m
Meaningful Marketing Insights - Parts 2 - 340m
주
3완료하는 데 2시간 필요
Data 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 readings, 1 quiz
3개의 읽기 자료
Data Preparation Instructions20m
Populating the Template20m
Review Forecasting Models for Marketing Decisions, Parts 1 - 310m
1개 연습문제
Logistic Regression Practice6m
주
4완료하는 데 1시간 필요
Model 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 reading, 2 quizzes
1개의 읽기 자료
Model Validation20m
1개 연습문제
Model Validation5m
강사
David Schweidel
Associate Professor of MarketingGoizueta Business School
에모리대학교 정보
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.
Foundations of Marketing Analytics 전문 분야 정보
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.
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