Marketing Analytics Capstone Project

Emory University via Coursera

Go to Course: https://www.coursera.org/learn/marketing-analytics-project

Introduction

## Course Review: Marketing Analytics Capstone Project on Coursera ### Overview The **Marketing Analytics Capstone Project** is a pivotal point for students who have completed the Foundations of Marketing Analytics specialization on Coursera. This hands-on project presents a significant opportunity to synthesize and apply the analytical techniques and strategies that participants have learned throughout the specialization. It emphasizes real-world application, engaging students in exploratory data analysis, model building, and predictive modeling to address marketing-related challenges. By the end of the course, students will have gained practical experience in resolving a marketing analytics problem using data-driven insights. ### Course Structure and Syllabus The course is efficiently structured across several key modules, each aimed at developing specific skills relevant to marketing analytics: 1. **Marketing Analytics Project Description** - The course kicks off with an overview of the project goals and activities, setting the stage for what learners will achieve during the capstone. 2. **Exploratory Analysis** - This foundational module focuses on understanding individual variables and their potential relationships with key outcomes, such as loan status. It cleverly integrates review content from previous courses, reinforcing important concepts. 3. **Data Preparation and Model Building** - Participants dive into the specifics of creating a classification model using logistic regression. This module emphasizes the importance of selecting predictor variables and introduces the hands-on aspect of model building, making it applicable to various marketing scenarios. 4. **Model Validation and Comparison** - Here, learners assess the accuracy of their models against baseline or naïve models, reflecting on model performance and the value of different predictors. This essential analysis is crucial for any marketing professional aiming to interpret data effectively. 5. **Incorporating Multiple Predictor Variables** - This advanced module challenges students to extend their logistics regression models and learn alternative evaluation techniques, further enriching their analytical toolkit. 6. **Congratulations!** - The course wraps up with a final congratulatory message from Professor David Schweidel, providing a sense of accomplishment and encouraging learners to share their newfound skills. ### Why You Should Enroll The **Marketing Analytics Capstone Project** is an invaluable experience for anyone looking to deepen their knowledge and proficiency in data analytics within the marketing landscape. Here are several compelling reasons to consider enrolling: - **Practical Application:** This course emphasizes hands-on projects that allow students to apply theoretical knowledge to real-world problems—ensuring skills are transferable to professional environments. - **Comprehensive Skill Development:** It not only enhances technical skills in data manipulation and model development but also fosters critical thinking and decision-making — essential skills for effective marketing professionals. - **Guidance from Experts:** The course is led by renowned instructors, including Professor David Schweidel, whose expertise enriches the learning experience. - **Collaborative Learning Environment:** Engaging with fellow learners through discussions and project collaboration can enhance understanding and inspire creative solutions to complex marketing problems. ### Recommendations To maximize your learning and ensure a smooth experience throughout the capstone, it is highly recommended to complete all preceding courses in the Foundations of Marketing Analytics specialization. This prior knowledge will provide you with necessary insights and background, making the capstone project a more enriching experience. ### Conclusion The **Marketing Analytics Capstone Project** on Coursera is a must-do for anyone serious about a career in marketing analytics. By embarking on this comprehensive project, you will not only solidify your analytical skills but also gain practical experience that can contribute significantly to your professional development. If you are ready to take your marketing analytics abilities to the next level, this course will undoubtedly set you up for success!

Syllabus

Marketing Analytics Project Description

This module will define the goals and activities for the marketing analytics capstone project.

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.

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.

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.

Incorporating Multiple Predictor Variables

In this module, we will generalize the logistic regression tool that was developed to include multiple predictor variables. We will also consider an alternative means of evaluating the performance of the model.

Congratulations!

This module provides a final congratulatory video from Professor David Schweidel.